LASSO for Covariate Selection

Published

February 11, 2026

Abstract

Using LASSO regression to select covariates for inclusion in analysis models

1 How I ran the LASSO

First, most of my approach was shaped by Fitzgerald Sice et al. (2023)

I primarily focused on baseline covariates for selection via LASSO. The only exceptions to this is survey day and whether the survey was on time or not, and the period of the survey done.

The document only shows results for 4 outcomes: PHQ2, GAD2, Total Consumption and Total Income. If we decide to move forward, I can add more outcomes to this list.

There are a few other things to keep in mind as well

\(\lambda\) selection
Grouping

Both of the above modify the selected covariates. One final note is that the typical approach is to run a Double LASSO; one to pick covariates that explain the outcome, and another set to pick treatment confounders. I do not show results for the latter regressions. Given that we randomized treatment, we would not expect many confounders to be selected and when running the code in preparation for this document, no covariates were selected.

1.1 Lambda Selection

The standard industry and research approach for picking \(\lambda\) — the regularization penalty term — is through cross-fitting. Some \(N\) \(\lambda\)’s are randomly selected (usually 100). Then, the data is split into \(K\) folds (usually 10) with the model being fit on the \(K-1\) folds and evaluated on the holdout fold. This is repeated for each fold and the average error across folds is calculated for each \(\lambda\). The \(\lambda\) that minimizes this error is selected. It is also standard practice to not pick the \(\lambda\) that minimizes error, but rather the largest \(\lambda\) within 1 standard error of the minimum. This approach is more conservative and results in fewer covariates being selected.

Another approach described in Chernozhukov, Hansen, and Spindler (2016) is to pick a data driven approach to selecting \(\lambda\). In their paper, they propose that their approach has better large sample properties than cross-fitting. In practice, their approach leads to larger (i.e. more conservative) \(\lambda\)’s being selected. I will briefly show results from both approaches but on the whole, I will use the cross-fitting approach for ease of implementation.

1.2 Grouping

A second decision to make is grouping. In particular, we can group covariates such that all or none of them are selected. In our case, this matters for district, period and community dummies. Without forced grouping, only a subset of the dummies are selected. With grouping, the LASSO still elects to control for district, community and period

Note

Note: some grouping is always done: particularly when handling missing values. To handle missing values, I first set all missing data to -99999 and then create a missing indicator for that variable that is set to 1. Any variable with missing data and its indicator are grouped together.

However, this grouping is not done for the rigorous \(\lambda\) seleciton as the package does not provide an option

2 Results

Code

```{r}
#| message: false
#| warning: false
#| label: setup-and-data

library(tidyverse)
library(haven)
library(kableExtra)
library(patchwork)
library(hdm)
library(grpreg)
library(fixest)
library(modelsummary)
library(oem)
library(dplyr)

conflicted::conflict_prefer("select", "dplyr")
conflicted::conflict_prefer("filter", "dplyr")

theme_set(theme_minimal())

drop_baseline_vars <- c(
    "schedule", "participant_id", "treatment",
    "treat", "pid", "control", "stable",
    "predictable", "unpredictable", "treated"
)

# Append _bl to all baseline covariates
baseline_covariates <- read_dta("/Users/st2246/Work/Pilot3/data/generated/main/transform/31_baseline_covariates-hh_id.dta") %>%
    select(-all_of(drop_baseline_vars)) %>%
    mutate(
        hh_id = as.factor(hh_id),
        community_id = as.factor(community_id),
        district_id = as.factor(district_id),
        wave = as.factor(wave),
        cohort = as.factor(cohort),
        across(
           .fns = ~ .^2,
           .cols = where(is.numeric),
           .names="{col}_SQUARED"
        ),
        across(
            .cols = where(anyNA),
            .fns = ~ as.integer(is.na(.)),
            .names = "{col}_MISSING"
        ),
        across(
            .cols = where(is.numeric),
            .fns = ~ replace_na(., -100)
        )
    ) %>%
    rename_with(~ paste0("bl_", .), -hh_id)
# Load data
df <- read_dta("/Users/st2246/Work/Pilot3/data/generated/main/transform/30_merged_panel-hh_id-period.dta") %>%
    mutate(
        treatment = as.factor(treatment),
        hh_id = as.factor(hh_id),
        community_id = as.factor(community_id),
        district_id = as.factor(district_id),
        period = as.factor(period),
        wave = as.factor(wave),
        cohort = as.factor(cohort),
    ) %>%
    filter(survey_completed == 1)

set.seed(123) # For reproducibility
```

Code

```{r}
#| message: false
#| warning: false
#| label: lasso-helpers

# Step by Step code to run Cross Validated Lasso
# First, prep data
exogenous_period_covariates <- c("period", "on_time", "day_of_week")
outcome_df <- df %>%
    left_join(baseline_covariates, by = "hh_id")

prep_outcome_lasso_data <- function(outcome_var, include_squares = FALSE) {
    subset_df <- outcome_df %>%
        filter(period != 0) %>%
        select(
            all_of(outcome_var),
            all_of(exogenous_period_covariates),
            all_of(starts_with("bl_"))
        ) %>%
        select(-matches("^bl.*_z$")) %>%
        filter(!is.na(.data[[outcome_var]]))
    subset_df <- if (include_squares) {
        subset_df
    } else {
        subset_df %>%
            select(-matches("_SQUARED$"))
    }

    outcome <- subset_df[[outcome_var]]
    covariates <- subset_df %>%
        select(-all_of(outcome_var)) %>%
        select(where(~ n_distinct(.) > 1)) %>%
        model.matrix(~ . - 1, data = .)

    # Subset the matrix to keep only variable columns
    non_constant_idx <- apply(covariates, 2, var) > 0
    covariates <- covariates[, non_constant_idx, drop = FALSE]

    # Rename columns to use :: separator for factor levels
    colnames(covariates) <- gsub("(bl_community_id|period|bl_district_id|bl_wave|bl_cohort)([0-9]+)$", "\\1::\\2", colnames(covariates))

    # Generate groupings that puts dummies together and missings
    labels <- colnames(covariates)
    labels <- sub("::.*", "", labels)
    labels <- gsub("_MISSING", "", labels)
    labels <- gsub("_SQUARED", "", labels)
    labels <- as.numeric(as.factor(labels))
    
    labels_no_dummies <- colnames(covariates)
    labels_no_dummies <- gsub("_MISSING", "", labels_no_dummies)
    labels_no_dummies <- gsub("_SQUARED", "", labels_no_dummies)
    labels_no_dummies <- as.numeric(as.factor(labels_no_dummies))
    
    return(list(covariates = covariates, outcome = outcome, labels=labels, labels_no_dummies=labels_no_dummies))
}

doMC::registerDoMC(cores = 10)
run_outcome_lasso_cv <- function(prep_data) {
    cv_lasso <- oem::cv.oem(
        x = prep_data$covariates, 
        y = prep_data$outcome, 
        groups=prep_data$labels_no_dummies, 
        penalty="grp.lasso",
        parallel = TRUE,
        ncores = 10
        )
    return(cv_lasso)
}

run_outcome_lasso_rig <- function(prep_data) {
    r_lasso <- rlasso(prep_data$covariates, prep_data$outcome, post = FALSE, intercept=TRUE)
    return(r_lasso)
}

run_grouped_lasso_cv <- function(prep_data) {
    cv_lasso <- oem::cv.oem(
        x = prep_data$covariates, 
        y = prep_data$outcome, 
        groups=prep_data$labels, 
        penalty = "grp.lasso",
        parallel = TRUE,
        ncores = 10
        )
    return(cv_lasso)
}



grp_lambda1se <- function(cv_fit) {
    #2. Identify the index of lambda.min
    i_min <- which.min(cv_fit$cve)
    # 3. Calculate the error threshold (Error at min + 1 SE)
    error_at_min <- cv_fit$cve[i_min]
    se_at_min <- cv_fit$cvse[i_min]
    threshold <- error_at_min + se_at_min
    # 4. Find lambda.1se
    # We look for the largest lambda (simplest model) where error is still below threshold
    # cv_fit$lambda is sorted from high to low, so we find the first index (highest lambda)
    # that satisfies the condition.
    eligible_indices <- which(cv_fit$cve <= threshold)
    i_1se <- min(eligible_indices) # standard glmnet logic uses the simplest model (highest lambda)
    lambda_1se <- cv_fit$lambda[i_1se]
    return(lambda_1se)
}

get_grpreg_nonzero_coefs <- function(grprep_lasso_model) {
    # Check if the model has a lambda.1se object; if not call grp_lambda1se
    lambda1 <- grprep_lasso_model$lambda.1se
    idx <- which.min(abs(grprep_lasso_model$lambda[[1]] - lambda1))
    coefs <- grprep_lasso_model$oem.fit$beta$grp.lasso[, idx] %>%
        as.matrix() %>%
        as.data.frame() %>%
        filter(V1 != 0) %>%
        rownames()
    return(coefs)
}

smart_coeffs <- function(clist) {
    clist <- clist[clist != "(Intercept)"]
    clist <- unique(sub("::.*", "", clist))
    return(clist)
}
```

Below are the selected covariates for GAD2 when using the different approaches.

Code

```{r}
#| message: false
#| warning: false
#| label: gad-lasso

prep_data <- prep_outcome_lasso_data("gad2_z")
gad_lasso <- prep_data %>% run_outcome_lasso_cv()
gad_rig_lasso <- prep_data %>% run_outcome_lasso_rig()
gad_grp_lasso <- prep_data %>%  run_grouped_lasso_cv()
```

Code

```{r}
clist <- get_grpreg_nonzero_coefs(gad_lasso)
# TODO: Look through allLabels named vector for each item in clist to get better variable names
clist <- map_chr(clist, ~ ifelse(is.na(allLabels[.]), ., allLabels[.]))
clist
```

 [1] "(Intercept)"                   "Period 1"                     
 [3] "Period 4"                      "Period 5"                     
 [5] "Endline"                       "bl_district_id::4"            
 [7] "bl_community_id::6"            "bl_community_id::8"           
 [9] "bl_community_id::12"           "bl_community_id::14"          
[11] "bl_community_id::16"           "bl_community_id::18"          
[13] "bl_community_id::19"           "bl_community_id::22"          
[15] "bl_community_id::23"           "bl_community_id::28"          
[17] "bl_community_id::41"           "bl_community_id::44"          
[19] "bl_community_id::45"           "bl_community_id::46"          
[21] "bl_community_id::51"           "bl_community_id::53"          
[23] "bl_community_id::57"           "bl_community_id::63"          
[25] "bl_community_id::68"           "bl_community_id::69"          
[27] "bl_community_id::70"           "bl_community_id::71"          
[29] "bl_community_id::74"           "bl_community_id::76"          
[31] "bl_community_id::79"           "bl_community_id::80"          
[33] "bl_community_id::82"           "bl_community_id::84"          
[35] "bl_community_id::88"           "bl_community_id::93"          
[37] "bl_community_id::95"           "bl_community_id::96"          
[39] "bl_community_id::98"           "bl_community_id::99"          
[41] "bl_community_id::100"          "bl_community_id::104"         
[43] "bl_community_id::107"          "bl_community_id::111"         
[45] "bl_community_id::118"          "No. Loans taken"              
[47] "Money lent out"                "Loans taken"                  
[49] "Cantril Ladder (present)"      "PHQ-8 Score"                  
[51] "GAD-7 Score"                   "PSS-10 Score"                 
[53] "PSWQ-16 Score"                 "Diener-5 Score"               
[55] "Mental Health Z-score Average" "bl_bp_tobacco"                
[57] "Systolic Blood Pressure"       "Participant Age"              
[59] "FI Z-score avg."               "FI Anderson Index"            
[61] "No. Incapacitated Members"     "bl_incapacitated_per_capita"  
[63] "Sharecropped Land"             "bl_cash_netflow_99"           
[65] "bl_total_consumption_99_pc"

Code

```{r}
clist_rig <- names(gad_rig_lasso$coefficients[gad_rig_lasso$coefficients != 0])
map_chr(clist_rig, ~ ifelse(is.na(allLabels[.]), ., allLabels[.]))
```

 [1] "(Intercept)"                   "Period 1"                     
 [3] "Period 4"                      "Period 5"                     
 [5] "Endline"                       "bl_district_id::4"            
 [7] "bl_community_id::8"            "bl_community_id::12"          
 [9] "bl_community_id::14"           "bl_community_id::16"          
[11] "bl_community_id::18"           "bl_community_id::22"          
[13] "bl_community_id::23"           "bl_community_id::28"          
[15] "bl_community_id::41"           "bl_community_id::44"          
[17] "bl_community_id::46"           "bl_community_id::51"          
[19] "bl_community_id::53"           "bl_community_id::57"          
[21] "bl_community_id::63"           "bl_community_id::68"          
[23] "bl_community_id::69"           "bl_community_id::70"          
[25] "bl_community_id::71"           "bl_community_id::74"          
[27] "bl_community_id::76"           "bl_community_id::80"          
[29] "bl_community_id::82"           "bl_community_id::84"          
[31] "bl_community_id::87"           "bl_community_id::93"          
[33] "bl_community_id::95"           "bl_community_id::96"          
[35] "bl_community_id::98"           "bl_community_id::99"          
[37] "bl_community_id::100"          "bl_community_id::104"         
[39] "bl_community_id::107"          "bl_community_id::111"         
[41] "bl_community_id::118"          "No. Loans taken"              
[43] "Money lent out"                "Loans taken"                  
[45] "Cantril Ladder (present)"      "PHQ-8 Score"                  
[47] "GAD-7 Score"                   "PSS-10 Score"                 
[49] "PSWQ-16 Score"                 "Diener-5 Score"               
[51] "Mental Health Z-score Average" "bl_bp_tobacco"                
[53] "Systolic Blood Pressure"       "Participant Age"              
[55] "FI Z-score avg."               "FI Anderson Index"            
[57] "No. Incapacitated Members"     "Sharecropped Land"            
[59] "bl_cash_netflow_99"            "bl_total_consumption_99_pc"   
[61] "bl_land_rent_value_MISSING"

Code

```{r}
clist_grp <- smart_coeffs(get_grpreg_nonzero_coefs(gad_grp_lasso))
map_chr(clist_grp, ~ ifelse(is.na(allLabels[.]), ., allLabels[.]))
```

 [1] "period"                                        
 [2] "bl_district_id"                                
 [3] "bl_community_id"                               
 [4] "Census Household Income Self Report (non win.)"
 [5] "No. Loans taken"                               
 [6] "Money lent out"                                
 [7] "Loans taken"                                   
 [8] "Days Worked (Participant)"                     
 [9] "Cantril Ladder (present)"                      
[10] "PHQ-8 Score"                                   
[11] "GAD-7 Score"                                   
[12] "PSS-10 Score"                                  
[13] "PSWQ-16 Score"                                 
[14] "Diener-5 Score"                                
[15] "bl_cantril_total"                              
[16] "Mental Health Z-score Average"                 
[17] "Sick or Injured person at BL"                  
[18] "bl_bp_tobacco"                                 
[19] "Systolic Blood Pressure"                       
[20] "Religious Event Shock"                         
[21] "bl_shock_other"                                
[22] "bl_shock_costs"                                
[23] "Participant Age"                               
[24] "Expenditure Non-Food Total"                    
[25] "bl_ls_owned_total"                             
[26] "bl_ls_bought_total"                            
[27] "bl_ls_gift_received_total_99"                  
[28] "FI Z-score avg."                               
[29] "FI Anderson Index"                             
[30] "bl_crop_stored_median_value"                   
[31] "No. Incapacitated Members"                     
[32] "bl_incapacitated_per_capita"                   
[33] "bl_land_rent_value"                            
[34] "Sharecropped Land"                             
[35] "bl_cash_inflow_pct_agincome"                   
[36] "bl_cash_netflow_99"                            
[37] "bl_total_consumption_99_pc"                    
[38] "bl_land_rent_value_MISSING"                    
[39] "bl_land_rent_value_SQUARED_MISSING"

Moving forward, I will use the cross-fitted grouped LASSO approach for covariate selection.

2.1 Treatment Effect Estimates vs Preliminary Analysis

Code

```{r}
#| message: false
#| warning: false
#| label: regression-functions

default_spec <-function(var) {
    fe_spec  <- "| district_id + period + wave + enum_id + day_of_week + cohort"
    controls <- paste0("bl_", var, " + hh_size + census_wealth_index") 
    return(as.formula(paste0(var, " ~ ", controls, " + i(treatment) ", fe_spec)))
}

original_regression <- function(var) {
    formula <- default_spec(var)
    model <- feols(
        formula,
        cluster = "hh_id",
        data = outcome_df %>% filter(period != 0)
    )
}

lasso_regression <- function(var, selected_vars) {
    selected_vars_transformed <- map_chr(selected_vars, ~ ifelse(
        grepl("^(bl_community_id|period|bl_district_id|bl_wave|bl_cohort)", .),
        paste0("i(", . ,")"),
        .
    ))
    controls <- paste(selected_vars, collapse = " + ")
    formula <- as.formula(paste0(var, " ~ ", controls, " + i(treatment) "))
    model <- feols(
        formula,
        cluster = "hh_id",
        data = outcome_df %>% filter(period != 0)
    )
    return(model)
}



makeTable <- function(models) {
    table <- modelsummary(models,
        escape = FALSE,
        output = "kableExtra",
        estimate = "{estimate}{stars}",
        statistic = "{std.error} ({conf.low}, {conf.high})",
        #coef_map = allLabels,
        coef_omit_sources = FALSE,
        stars = c(`***` = 0.01, `**` = 0.05, `*` = 0.1),
        gof_map = tribble(
            ~raw, ~clean, ~fmt,
            "nobs", "Observations", 0,
            "FE", "Community FE", 1,
        )
    ) %>%
        kable_classic(full_width = F, html_font = "Cambria", fixed_thead = T)
    table
}

compare_models <- function(var, selected_vars) {
    original_model <- original_regression(var)
    lasso_model <- lasso_regression(var, selected_vars)
    models <- list(
        "Preliminary Analysis" = original_model,
        "LASSO Selected Covariates" = lasso_model
    )
    table <- makeTable(models)
    return(table)
}
```

Code

```{r}
#| label: gad-regression
compare_models("gad2_z", smart_coeffs(get_grpreg_nonzero_coefs(gad_grp_lasso)))
```

NOTE: 62 observations removed because of NA values (LHS: 62).
NOTE: 62 observations removed because of NA values (LHS: 62).

The variables 'period6', 'bl_community_id83', 'bl_community_id118',
'bl_community_id119' and 'bl_land_rent_value_SQUARED_MISSING' have been removed
because of collinearity (see $collin.var).

Warning: The VCOV matrix is not positive semi-definite and was 'fixed' (see
?vcov).

	Preliminary Analysis	LASSO Selected Covariates
bl_gad2_z	0.099***
	0.011 (0.078, 0.121)
hh_size	−0.002
	0.004 (−0.010, 0.006)
census_wealth_index	−0.013
	0.017 (−0.047, 0.021)
treatment = 1	−0.060*	−0.085**
	0.037 (−0.132, 0.012)	0.036 (−0.155, −0.015)
treatment = 2	−0.028	−0.054
	0.037 (−0.100, 0.044)	0.036 (−0.123, 0.016)
treatment = 3	−0.060*	−0.086***
	0.031 (−0.122, 0.001)	0.030 (−0.146, −0.026)
(Intercept)		−0.346
		0.213 (−0.764, 0.071)
period1		−0.191***
		0.032 (−0.253, −0.129)
period2		−0.344***
		0.031 (−0.404, −0.283)
period3		−0.411***
		0.030 (−0.470, −0.351)
period4		−0.506***
		0.030 (−0.565, −0.447)
period5		−0.559***
		0.029 (−0.616, −0.502)
bl_district_id2		−0.009
		0.210 (−0.422, 0.403)
bl_district_id3		−0.076
		0.149 (−0.369, 0.216)
bl_district_id4		−0.056
		0.150 (−0.351, 0.238)
bl_community_id2		−0.290*
		0.157 (−0.598, 0.017)
bl_community_id3		−0.077
		0.155 (−0.381, 0.227)
bl_community_id4		−0.011
		0.195 (−0.393, 0.370)
bl_community_id5		0.039
		0.171 (−0.297, 0.375)
bl_community_id6		−0.034
		0.152 (−0.332, 0.265)
bl_community_id7		−0.128
		0.156 (−0.434, 0.178)
bl_community_id8		−0.038
		0.135 (−0.303, 0.228)
bl_community_id9		−0.424**
		0.210 (−0.836, −0.012)
bl_community_id10		−0.077
		0.226 (−0.520, 0.366)
bl_community_id11		−0.198
		0.210 (−0.608, 0.213)
bl_community_id12		−0.046
		0.130 (−0.301, 0.209)
bl_community_id13		−0.130
		0.142 (−0.408, 0.148)
bl_community_id14		0.121
		0.156 (−0.186, 0.428)
bl_community_id15		−0.165
		0.147 (−0.453, 0.123)
bl_community_id16		−0.367***
		0.131 (−0.625, −0.110)
bl_community_id17		−0.110
		0.133 (−0.371, 0.152)
bl_community_id18		−0.547**
		0.221 (−0.980, −0.114)
bl_community_id19		0.094
		0.220 (−0.338, 0.526)
bl_community_id20		−0.308
		0.232 (−0.763, 0.147)
bl_community_id21		−0.303
		0.208 (−0.711, 0.105)
bl_community_id22		0.147
		0.231 (−0.307, 0.600)
bl_community_id23		0.246
		0.209 (−0.165, 0.656)
bl_community_id24		−0.186
		0.213 (−0.603, 0.231)
bl_community_id25		0.007
		0.196 (−0.378, 0.392)
bl_community_id26		−0.116
		0.228 (−0.563, 0.331)
bl_community_id27		−0.070
		0.228 (−0.518, 0.378)
bl_community_id28		−0.429**
		0.209 (−0.839, −0.020)
bl_community_id29		−0.427
		0.273 (−0.963, 0.109)
bl_community_id30		−0.097
		0.232 (−0.552, 0.358)
bl_community_id31		−0.022
		0.279 (−0.570, 0.525)
bl_community_id33		−0.280
		0.223 (−0.716, 0.156)
bl_community_id34		−0.190
		0.207 (−0.595, 0.215)
bl_community_id35		−0.372
		0.254 (−0.871, 0.127)
bl_community_id36		−0.164
		0.211 (−0.577, 0.249)
bl_community_id37		−0.158
		0.223 (−0.595, 0.280)
bl_community_id38		−0.176
		0.218 (−0.603, 0.252)
bl_community_id39		0.050
		0.212 (−0.366, 0.466)
bl_community_id40		−0.294
		0.207 (−0.700, 0.112)
bl_community_id41		0.329
		0.272 (−0.205, 0.863)
bl_community_id42		−0.275
		0.213 (−0.693, 0.142)
bl_community_id43		−0.311
		0.205 (−0.714, 0.092)
bl_community_id44		0.185
		0.206 (−0.219, 0.590)
bl_community_id45		−0.364*
		0.193 (−0.742, 0.014)
bl_community_id46		0.125
		0.215 (−0.297, 0.547)
bl_community_id47		−0.101
		0.198 (−0.490, 0.288)
bl_community_id49		−0.178
		0.202 (−0.575, 0.218)
bl_community_id50		−0.163
		0.227 (−0.609, 0.283)
bl_community_id51		−0.514***
		0.195 (−0.896, −0.132)
bl_community_id52		−0.139
		0.191 (−0.514, 0.235)
bl_community_id53		−0.517***
		0.199 (−0.906, −0.127)
bl_community_id54		−0.225
		0.191 (−0.601, 0.150)
bl_community_id55		−0.279
		0.205 (−0.682, 0.123)
bl_community_id56		−0.018
		0.230 (−0.470, 0.434)
bl_community_id57		−0.543***
		0.193 (−0.921, −0.164)
bl_community_id58		−0.309*
		0.162 (−0.626, 0.008)
bl_community_id59		−0.254**
		0.114 (−0.477, −0.031)
bl_community_id60		−0.241
		0.147 (−0.528, 0.047)
bl_community_id61		0.036
		0.125 (−0.209, 0.281)
bl_community_id62		−0.103
		0.132 (−0.362, 0.155)
bl_community_id63		0.334**
		0.139 (0.062, 0.607)
bl_community_id64		0.016
		0.138 (−0.255, 0.287)
bl_community_id65		−0.193
		0.224 (−0.632, 0.245)
bl_community_id66		−0.122
		0.151 (−0.418, 0.174)
bl_community_id68		−0.496***
		0.133 (−0.756, −0.236)
bl_community_id69		−0.592**
		0.245 (−1.073, −0.112)
bl_community_id70		−0.596***
		0.120 (−0.832, −0.360)
bl_community_id71		−0.309**
		0.125 (−0.554, −0.064)
bl_community_id72		−0.162
		0.130 (−0.416, 0.092)
bl_community_id73		−0.104
		0.136 (−0.371, 0.163)
bl_community_id74		0.047
		0.132 (−0.213, 0.306)
bl_community_id75		−0.348**
		0.155 (−0.652, −0.045)
bl_community_id76		−0.357***
		0.124 (−0.601, −0.114)
bl_community_id77		−0.119
		0.124 (−0.363, 0.125)
bl_community_id78		−0.050
		0.133 (−0.312, 0.212)
bl_community_id79		0.065
		0.129 (−0.189, 0.318)
bl_community_id80		0.366***
		0.132 (0.108, 0.624)
bl_community_id81		−0.042
		0.144 (−0.324, 0.240)
bl_community_id82		0.063
		0.126 (−0.185, 0.310)
bl_community_id84		−0.556***
		0.159 (−0.868, −0.244)
bl_community_id85		−0.074
		0.131 (−0.330, 0.182)
bl_community_id86		−0.193
		0.144 (−0.476, 0.090)
bl_community_id87		−0.336**
		0.159 (−0.647, −0.025)
bl_community_id88		0.009
		0.139 (−0.262, 0.281)
bl_community_id89		−0.273*
		0.147 (−0.561, 0.015)
bl_community_id90		0.091
		0.191 (−0.284, 0.466)
bl_community_id91		−0.215
		0.150 (−0.509, 0.079)
bl_community_id92		−0.230*
		0.137 (−0.498, 0.038)
bl_community_id93		−0.505***
		0.127 (−0.755, −0.256)
bl_community_id94		−0.401***
		0.146 (−0.688, −0.114)
bl_community_id95		0.318*
		0.163 (−0.001, 0.637)
bl_community_id96		−0.627***
		0.166 (−0.953, −0.301)
bl_community_id97		−0.018
		0.133 (−0.279, 0.242)
bl_community_id98		0.139
		0.170 (−0.194, 0.472)
bl_community_id99		−0.488***
		0.146 (−0.775, −0.200)
bl_community_id100		0.361***
		0.136 (0.093, 0.629)
bl_community_id101		−0.360**
		0.146 (−0.646, −0.074)
bl_community_id102		−0.291*
		0.152 (−0.588, 0.007)
bl_community_id103		−0.013
		0.135 (−0.277, 0.252)
bl_community_id104		−0.442***
		0.135 (−0.707, −0.177)
bl_community_id105		−0.252
		0.167 (−0.578, 0.075)
bl_community_id106		−0.168
		0.183 (−0.527, 0.190)
bl_community_id107		−0.358**
		0.153 (−0.658, −0.058)
bl_community_id108		−0.318**
		0.143 (−0.597, −0.038)
bl_community_id109		−0.189
		0.171 (−0.524, 0.147)
bl_community_id110		−0.181
		0.125 (−0.426, 0.063)
bl_community_id111		−0.445***
		0.157 (−0.753, −0.137)
bl_community_id112		−0.191
		0.127 (−0.440, 0.057)
bl_community_id113		−0.093
		0.168 (−0.422, 0.236)
bl_community_id114		−0.259*
		0.153 (−0.560, 0.041)
bl_community_id115		−0.306**
		0.133 (−0.567, −0.044)
bl_community_id116		−0.163
		0.116 (−0.391, 0.064)
bl_community_id117		−0.111
		0.129 (−0.365, 0.143)
bl_census_hh_income_self_report		0.000
		0.000 (−0.000, 0.000)
bl_loans_taken		0.004
		0.014 (−0.024, 0.032)
bl_loan_total_lent		0.000**
		0.000 (0.000, 0.000)
bl_loan_total_outstanding_99		0.000
		0.000 (−0.000, 0.000)
bl_days_worked_participant		−0.007
		0.005 (−0.016, 0.003)
bl_cantril_present		−0.007
		0.010 (−0.026, 0.012)
bl_phq8		0.006
		0.004 (−0.001, 0.014)
bl_gad7		0.016***
		0.004 (0.008, 0.024)
bl_pss10		0.002
		0.003 (−0.004, 0.009)
bl_pswq16		0.004*
		0.002 (−0.000, 0.008)
bl_diener5		−0.002
		0.002 (−0.005, 0.002)
bl_cantril_total		−0.003
		0.006 (−0.014, 0.009)
bl_mental_health_average		0.031
		0.031 (−0.030, 0.091)
bl_med_sick_accident		−0.025
		0.035 (−0.094, 0.044)
bl_bp_tobacco		−0.129*
		0.068 (−0.262, 0.003)
bl_bp_systolic		0.001
		0.001 (−0.000, 0.002)
bl_shock_religious_event		−0.018
		0.036 (−0.089, 0.053)
bl_shock_other		−0.049
		0.102 (−0.249, 0.151)
bl_shock_costs		0.000
		0.000 (−0.000, 0.000)
bl_participant_age		0.009***
		0.001 (0.006, 0.011)
bl_expenditure_total_nonfood_99		−0.000
		0.000 (−0.000, 0.000)
bl_ls_owned_total		−0.000
		0.000 (−0.000, 0.000)
bl_ls_bought_total		−0.000**
		0.000 (−0.000, −0.000)
bl_ls_gift_received_total_99		0.002
		0.002 (−0.003, 0.006)
bl_fi_index		−0.024
		0.047 (−0.116, 0.068)
bl_fi_index_anderson		−0.033
		0.033 (−0.098, 0.032)
bl_crop_stored_median_value		−0.000
		0.000 (−0.000, 0.000)
bl_num_incapacitated_members		0.090***
		0.033 (0.026, 0.155)
bl_incapacitated_per_capita		0.001***
		0.000 (0.000, 0.001)
bl_land_rent_value		−0.000
		0.000 (−0.000, 0.000)
bl_land_sharecrop		−0.533***
		0.198 (−0.922, −0.144)
bl_cash_inflow_pct_agincome		−0.002
		0.002 (−0.005, 0.001)
bl_cash_netflow_99		−0.000**
		0.000 (−0.000, −0.000)
bl_total_consumption_99_pc		0.000
		0.000 (−0.000, 0.000)
bl_land_rent_value_MISSING		−0.586***
		0.134 (−0.849, −0.324)
Observations	12531	12531

Code

```{r}
#| label: phq-lasso
phq_prep_data <- prep_outcome_lasso_data("phq2_z")
phq_grp_lasso <- phq_prep_data %>% run_grouped_lasso_cv()
```

Code

```{r}
#| label: phq-regression
#| warning: false
compare_models("phq2_z", smart_coeffs(get_grpreg_nonzero_coefs(phq_grp_lasso)))
```

	Preliminary Analysis	LASSO Selected Covariates
bl_phq2_z	0.079***
	0.010 (0.059, 0.100)
hh_size	0.003
	0.004 (−0.005, 0.010)
census_wealth_index	−0.018
	0.017 (−0.051, 0.015)
treatment = 1	−0.071**	−0.088***
	0.035 (−0.138, −0.003)	0.034 (−0.154, −0.022)
treatment = 2	−0.035	−0.058*
	0.034 (−0.101, 0.032)	0.033 (−0.122, 0.007)
treatment = 3	−0.084***	−0.107***
	0.028 (−0.140, −0.028)	0.028 (−0.162, −0.053)
(Intercept)		−0.451**
		0.184 (−0.811, −0.091)
period1		−0.213***
		0.030 (−0.271, −0.155)
period2		−0.346***
		0.028 (−0.402, −0.291)
period3		−0.354***
		0.026 (−0.406, −0.302)
period4		−0.392***
		0.027 (−0.446, −0.339)
period5		−0.430***
		0.026 (−0.482, −0.379)
bl_district_id2		−0.076
		0.149 (−0.369, 0.217)
bl_district_id3		−0.107
		0.116 (−0.334, 0.121)
bl_district_id4		−0.091
		0.131 (−0.348, 0.166)
bl_community_id2		−0.536***
		0.144 (−0.819, −0.254)
bl_community_id3		−0.099
		0.175 (−0.442, 0.244)
bl_community_id4		−0.128
		0.166 (−0.454, 0.198)
bl_community_id5		−0.009
		0.178 (−0.357, 0.339)
bl_community_id6		−0.136
		0.148 (−0.426, 0.154)
bl_community_id7		−0.492***
		0.120 (−0.728, −0.257)
bl_community_id8		−0.082
		0.113 (−0.304, 0.139)
bl_community_id9		−0.216
		0.172 (−0.554, 0.122)
bl_community_id10		−0.116
		0.177 (−0.462, 0.231)
bl_community_id11		−0.203
		0.153 (−0.504, 0.098)
bl_community_id12		−0.182*
		0.109 (−0.395, 0.031)
bl_community_id13		0.049
		0.132 (−0.209, 0.308)
bl_community_id14		0.111
		0.141 (−0.165, 0.387)
bl_community_id15		−0.108
		0.119 (−0.341, 0.124)
bl_community_id16		−0.160
		0.115 (−0.386, 0.066)
bl_community_id17		−0.141
		0.124 (−0.383, 0.101)
bl_community_id18		−0.358*
		0.185 (−0.720, 0.005)
bl_community_id19		0.093
		0.161 (−0.223, 0.409)
bl_community_id20		−0.268*
		0.153 (−0.568, 0.032)
bl_community_id21		−0.092
		0.173 (−0.432, 0.248)
bl_community_id22		0.146
		0.160 (−0.166, 0.459)
bl_community_id23		0.001
		0.163 (−0.318, 0.320)
bl_community_id24		−0.211
		0.160 (−0.525, 0.102)
bl_community_id25		−0.267
		0.174 (−0.608, 0.074)
bl_community_id26		−0.036
		0.187 (−0.404, 0.331)
bl_community_id27		−0.034
		0.188 (−0.403, 0.335)
bl_community_id28		−0.316**
		0.155 (−0.620, −0.011)
bl_community_id29		−0.307*
		0.186 (−0.673, 0.059)
bl_community_id30		0.060
		0.178 (−0.289, 0.409)
bl_community_id31		0.002
		0.203 (−0.397, 0.400)
bl_community_id33		−0.204
		0.207 (−0.609, 0.202)
bl_community_id34		−0.074
		0.161 (−0.391, 0.242)
bl_community_id35		−0.388**
		0.192 (−0.764, −0.011)
bl_community_id36		0.015
		0.167 (−0.313, 0.343)
bl_community_id37		−0.175
		0.164 (−0.497, 0.146)
bl_community_id38		−0.161
		0.148 (−0.451, 0.129)
bl_community_id39		−0.333**
		0.139 (−0.606, −0.060)
bl_community_id40		−0.195
		0.164 (−0.517, 0.128)
bl_community_id41		0.373*
		0.222 (−0.062, 0.807)
bl_community_id42		−0.064
		0.157 (−0.371, 0.244)
bl_community_id43		−0.262
		0.171 (−0.597, 0.073)
bl_community_id44		0.070
		0.144 (−0.213, 0.354)
bl_community_id45		−0.221
		0.150 (−0.514, 0.073)
bl_community_id46		0.008
		0.141 (−0.269, 0.285)
bl_community_id47		−0.083
		0.159 (−0.394, 0.228)
bl_community_id49		−0.220
		0.195 (−0.602, 0.161)
bl_community_id50		−0.118
		0.161 (−0.434, 0.199)
bl_community_id51		−0.315**
		0.149 (−0.607, −0.024)
bl_community_id52		−0.134
		0.145 (−0.419, 0.151)
bl_community_id53		−0.230
		0.154 (−0.532, 0.073)
bl_community_id54		−0.141
		0.140 (−0.415, 0.134)
bl_community_id55		−0.266*
		0.141 (−0.542, 0.010)
bl_community_id56		0.132
		0.164 (−0.189, 0.453)
bl_community_id57		−0.376***
		0.144 (−0.658, −0.094)
bl_community_id58		−0.106
		0.164 (−0.428, 0.217)
bl_community_id59		−0.097
		0.121 (−0.333, 0.140)
bl_community_id60		0.119
		0.152 (−0.180, 0.418)
bl_community_id61		0.088
		0.107 (−0.122, 0.297)
bl_community_id62		0.266**
		0.125 (0.021, 0.511)
bl_community_id63		0.026
		0.161 (−0.289, 0.342)
bl_community_id64		0.198
		0.129 (−0.054, 0.451)
bl_community_id65		−0.140
		0.174 (−0.482, 0.201)
bl_community_id66		0.079
		0.148 (−0.211, 0.369)
bl_community_id68		−0.406***
		0.117 (−0.634, −0.177)
bl_community_id69		−0.508***
		0.157 (−0.816, −0.199)
bl_community_id70		−0.311***
		0.118 (−0.542, −0.079)
bl_community_id71		−0.030
		0.105 (−0.236, 0.175)
bl_community_id72		0.122
		0.114 (−0.101, 0.346)
bl_community_id73		0.025
		0.113 (−0.197, 0.247)
bl_community_id74		0.198*
		0.107 (−0.011, 0.408)
bl_community_id75		−0.198
		0.142 (−0.477, 0.081)
bl_community_id76		−0.218**
		0.099 (−0.411, −0.024)
bl_community_id77		0.032
		0.121 (−0.206, 0.270)
bl_community_id78		0.082
		0.105 (−0.124, 0.287)
bl_community_id79		0.063
		0.090 (−0.114, 0.239)
bl_community_id80		0.361***
		0.103 (0.160, 0.562)
bl_community_id81		−0.107
		0.122 (−0.345, 0.132)
bl_community_id82		−0.024
		0.103 (−0.225, 0.178)
bl_community_id84		−0.439***
		0.138 (−0.710, −0.167)
bl_community_id85		−0.124
		0.141 (−0.401, 0.154)
bl_community_id86		−0.127
		0.160 (−0.441, 0.186)
bl_community_id87		−0.335*
		0.178 (−0.684, 0.015)
bl_community_id88		−0.132
		0.130 (−0.387, 0.124)
bl_community_id89		−0.172
		0.144 (−0.454, 0.110)
bl_community_id90		0.126
		0.119 (−0.107, 0.358)
bl_community_id91		−0.121
		0.158 (−0.431, 0.188)
bl_community_id92		−0.163
		0.125 (−0.408, 0.082)
bl_community_id93		−0.311**
		0.130 (−0.566, −0.056)
bl_community_id94		−0.482***
		0.175 (−0.825, −0.138)
bl_community_id95		0.304*
		0.173 (−0.036, 0.643)
bl_community_id96		−0.346**
		0.150 (−0.640, −0.053)
bl_community_id97		0.074
		0.131 (−0.183, 0.332)
bl_community_id98		−0.052
		0.153 (−0.351, 0.247)
bl_community_id99		−0.131
		0.141 (−0.408, 0.145)
bl_community_id100		0.335*
		0.187 (−0.032, 0.701)
bl_community_id101		−0.392***
		0.123 (−0.634, −0.150)
bl_community_id102		−0.221
		0.143 (−0.500, 0.059)
bl_community_id103		0.042
		0.131 (−0.215, 0.300)
bl_community_id104		−0.416***
		0.131 (−0.674, −0.158)
bl_community_id105		−0.280*
		0.148 (−0.569, 0.010)
bl_community_id106		−0.116
		0.215 (−0.539, 0.306)
bl_community_id107		−0.221
		0.137 (−0.490, 0.047)
bl_community_id108		−0.114
		0.130 (−0.368, 0.140)
bl_community_id109		0.001
		0.128 (−0.249, 0.251)
bl_community_id110		−0.109
		0.133 (−0.369, 0.151)
bl_community_id111		−0.415***
		0.133 (−0.676, −0.155)
bl_community_id112		−0.097
		0.128 (−0.348, 0.154)
bl_community_id113		−0.026
		0.157 (−0.333, 0.281)
bl_community_id114		−0.194
		0.145 (−0.478, 0.089)
bl_community_id115		−0.166
		0.129 (−0.420, 0.088)
bl_community_id116		−0.167
		0.108 (−0.379, 0.044)
bl_community_id117		−0.053
		0.123 (−0.293, 0.188)
bl_cohort2		0.018
		0.026 (−0.034, 0.070)
bl_census_hh_income_self_report		0.000
		0.000 (−0.000, 0.000)
bl_loans_taken		0.015
		0.013 (−0.010, 0.040)
bl_loan_total_payment		0.000***
		0.000 (0.000, 0.000)
bl_loan_total_lent		0.000***
		0.000 (0.000, 0.000)
bl_loan_total_outstanding_99		0.000
		0.000 (−0.000, 0.000)
bl_food_purchase_total_phone		0.000
		0.000 (−0.000, 0.000)
bl_days_worked_participant		−0.008*
		0.005 (−0.017, 0.001)
bl_cantril_present		−0.006
		0.005 (−0.015, 0.003)
bl_phq2		0.021*
		0.011 (−0.002, 0.043)
bl_gad7		0.019***
		0.004 (0.012, 0.027)
bl_pss10		0.005
		0.003 (−0.001, 0.010)
bl_pswq16		0.005**
		0.002 (0.001, 0.008)
bl_diener5		−0.001
		0.002 (−0.005, 0.002)
bl_mental_health_average		−0.021
		0.035 (−0.090, 0.049)
bl_med_sick_accident		0.007
		0.032 (−0.057, 0.071)
bl_shock_costs		0.000**
		0.000 (0.000, 0.000)
bl_participant_age		0.008***
		0.001 (0.005, 0.010)
bl_share_elderly		−0.299
		0.187 (−0.665, 0.067)
bl_ls_bought_total_99		0.001
		0.000 (−0.000, 0.001)
bl_dg_buy_total_value		−0.000***
		0.000 (−0.000, −0.000)
bl_fi_index		−0.004
		0.045 (−0.092, 0.084)
bl_fi_index_anderson		−0.050
		0.031 (−0.111, 0.012)
bl_expenditure_total_food_99		−0.000
		0.000 (−0.000, 0.000)
bl_num_incapacitated_members		0.044
		0.030 (−0.014, 0.103)
bl_land_rent_value		−0.000
		0.000 (−0.000, 0.000)
bl_land_own_farm_value		0.000
		0.000 (−0.000, 0.000)
bl_cash_outflow_99		−0.000
		0.000 (−0.000, 0.000)
bl_cash_outflow_pct_agequipment		0.004
		0.004 (−0.003, 0.011)
bl_cash_outflow_pct_lent		−0.007***
		0.003 (−0.013, −0.002)
bl_cash_netflow_99		−0.000*
		0.000 (−0.000, 0.000)
bl_land_rent_value_MISSING		−0.529**
		0.248 (−1.015, −0.043)
Observations	12531	12531

Code

```{r}
#| label: income-regression
#| warning: false
income_grp_lasso <- run_grouped_lasso_cv(prep_outcome_lasso_data("total_income_99"))
compare_models("total_income_99", smart_coeffs(get_grpreg_nonzero_coefs(income_grp_lasso)))
```

	Preliminary Analysis	LASSO Selected Covariates
bl_total_income_99	0.035***
	0.008 (0.019, 0.051)
hh_size	3.076*
	1.714 (−0.285, 6.437)
census_wealth_index	35.963***
	7.996 (20.283, 51.643)
treatment = 1	−25.115*	−14.684
	15.008 (−54.545, 4.316)	14.995 (−44.089, 14.721)
treatment = 2	18.379	17.304
	16.462 (−13.903, 50.661)	16.496 (−15.045, 49.654)
treatment = 3	−10.901	−10.041
	13.109 (−36.609, 14.806)	13.412 (−36.341, 16.259)
(Intercept)		256.255***
		34.052 (189.479, 323.030)
period1		−140.122***
		14.504 (−168.564, −111.680)
period2		−159.311***
		13.500 (−185.783, −132.838)
period3		−176.988***
		13.032 (−202.544, −151.432)
period4		−164.894***
		13.015 (−190.417, −139.370)
period5		−163.009***
		13.054 (−188.607, −137.410)
bl_district_id2		−116.040***
		18.950 (−153.201, −78.879)
bl_district_id3		−71.094***
		21.452 (−113.162, −29.026)
bl_district_id4		−93.583***
		19.075 (−130.989, −56.177)
bl_wave2		40.160***
		9.323 (21.876, 58.443)
bl_census_hh_income_self_report		0.005
		0.013 (−0.020, 0.030)
bl_census_wealth_index		24.501***
		7.979 (8.855, 40.147)
bl_census_hh_income_self_report_99		0.004
		0.016 (−0.028, 0.036)
bl_loan_total_lent		0.053**
		0.026 (0.002, 0.105)
bl_food_purchase_total_bl		0.022
		0.017 (−0.010, 0.055)
bl_diener5		0.648
		1.679 (−2.644, 3.940)
bl_diener3		1.320
		2.393 (−3.373, 6.013)
bl_mental_health_average		21.526***
		6.478 (8.823, 34.229)
bl_med_assistance_received		13.508
		11.866 (−9.761, 36.778)
bl_shock_death_livestock		14.621
		10.036 (−5.059, 34.301)
bl_shock_religious_event		23.559**
		11.301 (1.399, 45.720)
bl_num_adults		9.420**
		4.390 (0.811, 18.029)
bl_avg_education_years		−3.989*
		2.157 (−8.219, 0.241)
bl_expenditure_total_nonfood_99		0.007
		0.027 (−0.045, 0.059)
bl_dg_own_total_value_99		0.002***
		0.001 (0.000, 0.003)
bl_svg_current_savings		0.009
		0.007 (−0.005, 0.023)
bl_svg_withdrawals_99		0.025
		0.044 (−0.061, 0.111)
bl_total_consumption_99		0.012
		0.019 (−0.025, 0.050)
bl_cash_inflow_99		−0.010
		0.009 (−0.027, 0.007)
bl_cash_inflow_pct_cropsale		0.408
		0.268 (−0.117, 0.933)
bl_cash_inflow_pct_agincome		1.376
		1.054 (−0.690, 3.442)
bl_cash_inflow_pct_gifts		0.875**
		0.350 (0.189, 1.562)
bl_cash_outflow_99		0.002
		0.016 (−0.029, 0.032)
bl_total_income_99_pc		0.245**
		0.105 (0.039, 0.451)
Observations	12593	12593

Code

```{r}
#| label: consumption-regression
#| warning: false
cons_grp_lasso <- run_grouped_lasso_cv(prep_outcome_lasso_data("total_consumption_99"))
compare_models("total_consumption_99", smart_coeffs(get_grpreg_nonzero_coefs(cons_grp_lasso)))
```

	Preliminary Analysis	LASSO Selected Covariates
bl_total_consumption_99	0.142***	0.036
	0.009 (0.124, 0.160)	0.073 (−0.106, 0.179)
hh_size	13.560***
	2.277 (9.095, 18.024)
census_wealth_index	24.902**
	9.782 (5.719, 44.084)
treatment = 1	71.600***	59.816***
	19.322 (33.709, 109.492)	17.942 (24.632, 95.001)
treatment = 2	72.977***	47.744**
	18.825 (36.062, 109.893)	18.676 (11.121, 84.367)
treatment = 3	65.175***	44.139***
	15.447 (34.884, 95.467)	14.604 (15.501, 72.777)
(Intercept)		258.351***
		95.576 (70.925, 445.777)
period1		−57.237***
		16.568 (−89.727, −24.747)
period2		−269.336***
		14.579 (−297.927, −240.746)
period3		−339.840***
		13.961 (−367.218, −312.462)
period4		−394.072***
		13.585 (−420.712, −367.431)
period5		−424.560***
		13.611 (−451.251, −397.869)
on_time		16.943*
		8.664 (−0.047, 33.932)
bl_district_id2		17.239
		85.887 (−151.186, 185.664)
bl_district_id3		103.700
		84.730 (−62.456, 269.856)
bl_district_id4		108.021
		84.839 (−58.350, 274.391)
bl_community_id2		168.946*
		100.827 (−28.776, 366.668)
bl_community_id3		−14.720
		111.623 (−233.614, 204.174)
bl_community_id4		120.355
		116.004 (−107.129, 347.840)
bl_community_id5		75.168
		91.979 (−105.203, 255.539)
bl_community_id6		82.793
		108.966 (−130.891, 296.476)
bl_community_id7		−72.942
		101.456 (−271.898, 126.014)
bl_community_id8		−75.452
		83.360 (−238.922, 88.019)
bl_community_id9		341.555*
		199.208 (−49.094, 732.203)
bl_community_id10		194.019
		127.751 (−56.502, 444.539)
bl_community_id11		181.533**
		88.674 (7.643, 355.424)
bl_community_id12		68.273
		85.985 (−100.344, 236.891)
bl_community_id13		175.193*
		101.684 (−24.211, 374.597)
bl_community_id14		−58.239
		96.017 (−246.530, 130.052)
bl_community_id15		164.962*
		95.625 (−22.560, 352.484)
bl_community_id16		189.798**
		89.247 (14.784, 364.812)
bl_community_id17		19.782
		84.566 (−146.053, 185.616)
bl_community_id18		8.567
		80.671 (−149.629, 166.763)
bl_community_id19		−15.252
		71.070 (−154.621, 124.117)
bl_community_id20		1.635
		83.458 (−162.027, 165.297)
bl_community_id21		24.810
		53.817 (−80.725, 130.345)
bl_community_id22		61.317
		97.654 (−130.183, 252.818)
bl_community_id23		−2.560
		93.647 (−186.204, 181.084)
bl_community_id24		15.357
		59.141 (−100.620, 131.334)
bl_community_id25		210.242*
		115.200 (−15.667, 436.150)
bl_community_id26		120.197
		76.301 (−29.429, 269.824)
bl_community_id27		19.093
		134.054 (−243.789, 281.975)
bl_community_id28		−29.167
		56.445 (−139.855, 81.522)
bl_community_id29		−72.955
		73.672 (−217.426, 71.517)
bl_community_id30		123.659*
		66.181 (−6.123, 253.441)
bl_community_id31		118.503
		135.586 (−147.383, 384.390)
bl_community_id33		−82.785
		55.962 (−192.526, 26.956)
bl_community_id34		165.615**
		84.132 (0.631, 330.598)
bl_community_id35		−65.323
		75.462 (−213.304, 82.658)
bl_community_id36		−28.286
		57.752 (−141.538, 84.966)
bl_community_id37		156.873**
		67.576 (24.355, 289.391)
bl_community_id38		13.346
		59.845 (−104.012, 130.703)
bl_community_id39		18.346
		95.159 (−168.262, 204.954)
bl_community_id40		−104.145*
		60.639 (−223.059, 14.769)
bl_community_id41		61.928
		76.704 (−88.489, 212.344)
bl_community_id42		70.743
		61.468 (−49.795, 191.282)
bl_community_id43		100.296
		64.543 (−26.274, 226.865)
bl_community_id44		−37.940
		64.187 (−163.812, 87.932)
bl_community_id45		−23.005
		72.602 (−165.378, 119.369)
bl_community_id46		−15.613
		64.468 (−142.035, 110.809)
bl_community_id47		69.021
		55.225 (−39.276, 177.318)
bl_community_id49		419.272***
		142.380 (140.064, 698.481)
bl_community_id50		34.227
		76.655 (−116.094, 184.548)
bl_community_id51		2.425
		69.024 (−132.932, 137.782)
bl_community_id52		29.046
		75.045 (−118.117, 176.210)
bl_community_id53		17.359
		58.799 (−97.947, 132.665)
bl_community_id54		57.426
		64.722 (−69.495, 184.347)
bl_community_id55		34.602
		63.026 (−88.993, 158.196)
bl_community_id56		78.128
		77.443 (−73.739, 229.994)
bl_community_id57		55.816
		72.398 (−86.158, 197.789)
bl_community_id58		−234.679***
		64.376 (−360.921, −108.436)
bl_community_id59		−251.770***
		57.997 (−365.503, −138.037)
bl_community_id60		−39.752
		87.625 (−211.586, 132.082)
bl_community_id61		−69.818
		68.573 (−204.290, 64.655)
bl_community_id62		−271.116***
		59.512 (−387.819, −154.413)
bl_community_id63		5.301
		70.855 (−133.646, 144.248)
bl_community_id64		−79.398
		71.922 (−220.438, 61.641)
bl_community_id65		−33.486
		76.649 (−183.795, 116.824)
bl_community_id66		−204.168***
		69.186 (−339.843, −68.494)
bl_community_id68		−104.604*
		58.953 (−220.212, 11.003)
bl_community_id69		−290.425***
		63.994 (−415.919, −164.932)
bl_community_id70		−96.556*
		54.956 (−204.325, 11.213)
bl_community_id71		−267.783***
		51.938 (−369.634, −165.932)
bl_community_id72		−218.135***
		65.618 (−346.812, −89.458)
bl_community_id73		−259.240***
		76.617 (−409.486, −108.993)
bl_community_id74		−137.364*
		70.371 (−275.363, 0.634)
bl_community_id75		−28.088
		69.948 (−165.257, 109.080)
bl_community_id76		−130.437**
		55.272 (−238.827, −22.047)
bl_community_id77		−53.063
		62.079 (−174.801, 68.674)
bl_community_id78		−100.173*
		60.678 (−219.163, 18.817)
bl_community_id79		−45.447
		61.427 (−165.907, 75.013)
bl_community_id80		−84.203
		63.155 (−208.051, 39.645)
bl_community_id81		72.213
		63.213 (−51.749, 196.176)
bl_community_id82		−62.994
		60.496 (−181.627, 55.639)
bl_community_id84		−99.055
		97.295 (−289.852, 91.742)
bl_community_id85		−40.542
		59.469 (−157.162, 76.078)
bl_community_id86		101.072
		84.618 (−64.864, 267.009)
bl_community_id87		184.121*
		94.892 (−1.964, 370.206)
bl_community_id88		129.687*
		74.692 (−16.785, 276.160)
bl_community_id89		−70.276
		60.394 (−188.708, 48.156)
bl_community_id90		−105.744
		109.982 (−321.420, 109.931)
bl_community_id91		−107.084
		71.723 (−247.733, 33.564)
bl_community_id92		76.568
		95.441 (−110.593, 263.729)
bl_community_id93		166.483**
		69.785 (29.634, 303.333)
bl_community_id94		36.347
		89.975 (−140.094, 212.789)
bl_community_id95		10.341
		97.576 (−181.007, 201.688)
bl_community_id96		17.694
		82.118 (−143.340, 178.729)
bl_community_id97		−111.798
		78.350 (−265.443, 41.847)
bl_community_id98		−45.654
		100.402 (−242.543, 151.236)
bl_community_id99		−30.175
		83.007 (−192.953, 132.602)
bl_community_id100		−95.443
		74.114 (−240.780, 49.895)
bl_community_id101		52.623
		89.869 (−123.612, 228.857)
bl_community_id102		−145.194***
		56.261 (−255.522, −34.867)
bl_community_id103		−130.457
		82.796 (−292.822, 31.908)
bl_community_id104		−108.532
		67.198 (−240.308, 23.245)
bl_community_id105		−67.163
		91.982 (−247.541, 113.215)
bl_community_id106		13.392
		88.633 (−160.418, 187.202)
bl_community_id107		128.008
		84.321 (−37.345, 293.362)
bl_community_id108		−139.374*
		77.841 (−292.022, 13.274)
bl_community_id109		32.722
		94.060 (−151.731, 217.174)
bl_community_id110		−16.395
		76.816 (−167.031, 134.241)
bl_community_id111		−90.019
		63.054 (−213.668, 33.630)
bl_community_id112		−27.020
		73.687 (−171.522, 117.481)
bl_community_id113		78.801
		75.251 (−68.767, 226.370)
bl_community_id114		−122.306**
		56.365 (−232.838, −11.774)
bl_community_id115		−117.588
		76.923 (−268.435, 33.259)
bl_community_id116		−19.055
		58.203 (−133.191, 95.081)
bl_community_id117		−43.414
		60.203 (−161.474, 74.645)
bl_hh_size		−0.962
		6.515 (−13.739, 11.814)
bl_cohort2		−17.183
		14.960 (−46.519, 12.153)
bl_census_num_eating_groups		59.687***
		20.799 (18.899, 100.474)
bl_census_wealth_index		15.890
		10.095 (−3.906, 35.686)
bl_loans_taken		8.840
		6.012 (−2.949, 20.629)
bl_loan_total_lent		0.067***
		0.021 (0.026, 0.107)
bl_food_purchase_total_99		0.079
		0.075 (−0.067, 0.226)
bl_food_consumption_total_99		0.026*
		0.014 (−0.001, 0.054)
bl_days_worked_participant		3.517
		3.350 (−3.053, 10.088)
bl_cantril_present		5.203**
		2.637 (0.031, 10.375)
bl_phq8		1.440
		2.546 (−3.552, 6.432)
bl_phq2		1.464
		7.240 (−12.734, 15.663)
bl_gad7		1.140
		2.284 (−3.339, 5.619)
bl_diener5		0.406
		1.018 (−1.589, 2.402)
bl_mental_health_average		16.338
		15.278 (−13.622, 46.299)
bl_bp_excercise		−62.834*
		33.518 (−128.563, 2.895)
bl_med_assistance_received		31.428**
		14.542 (2.912, 59.945)
bl_shock_death_relative		12.830
		13.092 (−12.844, 38.503)
bl_shock_death_livestock		17.044
		13.784 (−9.986, 44.073)
bl_shock_religious_event		31.969*
		18.951 (−5.194, 69.131)
bl_shock_accident_injury		36.031**
		14.367 (7.857, 64.205)
bl_num_children		20.715**
		8.710 (3.635, 37.795)
bl_num_migrated		−10.639
		11.034 (−32.277, 11.000)
bl_participant_age		2.472***
		0.686 (1.126, 3.817)
bl_avg_age		1.830
		1.301 (−0.722, 4.382)
bl_expenditure_total_nonfood		−0.043**
		0.019 (−0.079, −0.006)
bl_expenditure_total_nonfood_99		0.078
		0.081 (−0.080, 0.236)
bl_gifts_food_sent		0.233*
		0.120 (−0.002, 0.468)
bl_gifts_cash_sent		−0.077**
		0.033 (−0.142, −0.013)
bl_ls_gift_given_total		0.403
		0.351 (−0.286, 1.091)
bl_ls_bought_total_99		0.290
		0.230 (−0.161, 0.741)
bl_ls_gift_given_total_99		0.500
		1.026 (−1.512, 2.512)
bl_dg_own_total_value_99		0.001
		0.001 (−0.001, 0.003)
bl_ag_eqp_sale_total_value		0.825**
		0.399 (0.044, 1.607)
bl_fi_index_anderson		6.967
		6.010 (−4.818, 18.752)
bl_expenditure_total_food		−0.002
		0.009 (−0.019, 0.015)
bl_expenditure_total_food_99		0.035
		0.026 (−0.017, 0.086)
bl_svg_withdrawals_99		0.140***
		0.052 (0.038, 0.242)
bl_crop_stored_median_value		−0.000
		0.000 (−0.001, 0.000)
bl_other_income_remittance		0.174
		0.107 (−0.036, 0.384)
bl_land_rent_value		−0.077
		0.078 (−0.230, 0.076)
bl_asset_sales_99		0.093*
		0.048 (−0.000, 0.186)
bl_cash_outflow_pct_gifts		−1.539
		1.720 (−4.913, 1.835)
bl_cash_outflow_pct_lent		−3.936**
		1.832 (−7.528, −0.345)
bl_cash_netflow_99		−0.024***
		0.007 (−0.038, −0.010)
bl_gifts_food_sent_MISSING		−163.860**
		68.124 (−297.453, −30.268)
bl_expenditure_total_food_MISSING		−115.734***
		39.339 (−192.878, −38.591)
bl_land_rent_value_MISSING		−244.675***
		77.395 (−396.447, −92.902)
Observations	12593	12593

3 Appendix

3.1 More complete LASSO

The results below include lasso selected values out of a set that includes squared terms as well.

Code

```{r}
#| label: gad-lasso-square
#| warning: false
gad_grp_lasso_sq <- run_grouped_lasso_cv(prep_outcome_lasso_data("gad2_z", T))

original_model <- original_regression("gad2_z")
lasso_model <- lasso_regression("gad2_z", smart_coeffs(get_grpreg_nonzero_coefs(gad_grp_lasso)))
lasso_model_sq <- lasso_regression("gad2_z", smart_coeffs(get_grpreg_nonzero_coefs(gad_grp_lasso_sq)))

models <- list(
    "Preliminary Analysis" = original_model,
    "LASSO Selected" = lasso_model,
    "LASSO Selected (w/ Squares)" = lasso_model_sq
)
makeTable(models)
```

	Preliminary Analysis	LASSO Selected	LASSO Selected (w/ Squares)
bl_gad2_z	0.099***
	0.011 (0.078, 0.121)
hh_size	−0.002
	0.004 (−0.010, 0.006)
census_wealth_index	−0.013
	0.017 (−0.047, 0.021)
treatment = 1	−0.060*	−0.085**	−0.088**
	0.037 (−0.132, 0.012)	0.036 (−0.155, −0.015)	0.036 (−0.158, −0.018)
treatment = 2	−0.028	−0.054	−0.046
	0.037 (−0.100, 0.044)	0.036 (−0.123, 0.016)	0.035 (−0.115, 0.023)
treatment = 3	−0.060*	−0.086***	−0.076**
	0.031 (−0.122, 0.001)	0.030 (−0.146, −0.026)	0.030 (−0.135, −0.017)
(Intercept)		−0.346	−7807.039
		0.213 (−0.764, 0.071)	12947.961 (−33198.150, 17584.072)
period1		−0.191***	−0.192***
		0.032 (−0.253, −0.129)	0.032 (−0.254, −0.130)
period2		−0.344***	−0.344***
		0.031 (−0.404, −0.283)	0.031 (−0.405, −0.283)
period3		−0.411***	−0.411***
		0.030 (−0.470, −0.351)	0.030 (−0.470, −0.352)
period4		−0.506***	−0.507***
		0.030 (−0.565, −0.447)	0.030 (−0.566, −0.448)
period5		−0.559***	−0.559***
		0.029 (−0.616, −0.502)	0.029 (−0.617, −0.502)
bl_district_id2		−0.009	−0.042
		0.210 (−0.422, 0.403)	0.224 (−0.482, 0.398)
bl_district_id3		−0.076	−0.067
		0.149 (−0.369, 0.216)	0.161 (−0.383, 0.248)
bl_district_id4		−0.056	−0.089
		0.150 (−0.351, 0.238)	0.157 (−0.397, 0.219)
bl_community_id2		−0.290*	−0.257
		0.157 (−0.598, 0.017)	0.169 (−0.587, 0.074)
bl_community_id3		−0.077	−0.101
		0.155 (−0.381, 0.227)	0.163 (−0.421, 0.220)
bl_community_id4		−0.011	−0.023
		0.195 (−0.393, 0.370)	0.206 (−0.427, 0.382)
bl_community_id5		0.039	0.015
		0.171 (−0.297, 0.375)	0.179 (−0.336, 0.365)
bl_community_id6		−0.034	−0.065
		0.152 (−0.332, 0.265)	0.165 (−0.389, 0.259)
bl_community_id7		−0.128	−0.130
		0.156 (−0.434, 0.178)	0.167 (−0.457, 0.196)
bl_community_id8		−0.038	−0.014
		0.135 (−0.303, 0.228)	0.148 (−0.305, 0.277)
bl_community_id9		−0.424**	−0.457**
		0.210 (−0.836, −0.012)	0.220 (−0.888, −0.026)
bl_community_id10		−0.077	−0.005
		0.226 (−0.520, 0.366)	0.247 (−0.489, 0.478)
bl_community_id11		−0.198	−0.227
		0.210 (−0.608, 0.213)	0.213 (−0.645, 0.190)
bl_community_id12		−0.046	−0.085
		0.130 (−0.301, 0.209)	0.144 (−0.368, 0.198)
bl_community_id13		−0.130	−0.144
		0.142 (−0.408, 0.148)	0.154 (−0.445, 0.158)
bl_community_id14		0.121	0.100
		0.156 (−0.186, 0.428)	0.168 (−0.230, 0.430)
bl_community_id15		−0.165	−0.177
		0.147 (−0.453, 0.123)	0.160 (−0.491, 0.138)
bl_community_id16		−0.367***	−0.392***
		0.131 (−0.625, −0.110)	0.143 (−0.673, −0.111)
bl_community_id17		−0.110	−0.117
		0.133 (−0.371, 0.152)	0.145 (−0.400, 0.167)
bl_community_id18		−0.547**	−0.524**
		0.221 (−0.980, −0.114)	0.226 (−0.967, −0.081)
bl_community_id19		0.094	0.087
		0.220 (−0.338, 0.526)	0.225 (−0.355, 0.529)
bl_community_id20		−0.308	−0.277
		0.232 (−0.763, 0.147)	0.240 (−0.749, 0.194)
bl_community_id21		−0.303	−0.243
		0.208 (−0.711, 0.105)	0.214 (−0.664, 0.177)
bl_community_id22		0.147	0.046
		0.231 (−0.307, 0.600)	0.245 (−0.434, 0.527)
bl_community_id23		0.246	0.276
		0.209 (−0.165, 0.656)	0.220 (−0.156, 0.708)
bl_community_id24		−0.186	−0.166
		0.213 (−0.603, 0.231)	0.216 (−0.588, 0.257)
bl_community_id25		0.007	0.078
		0.196 (−0.378, 0.392)	0.202 (−0.318, 0.473)
bl_community_id26		−0.116	−0.076
		0.228 (−0.563, 0.331)	0.229 (−0.525, 0.373)
bl_community_id27		−0.070	−0.018
		0.228 (−0.518, 0.378)	0.236 (−0.480, 0.443)
bl_community_id28		−0.429**	−0.432**
		0.209 (−0.839, −0.020)	0.212 (−0.848, −0.016)
bl_community_id29		−0.427	−0.432
		0.273 (−0.963, 0.109)	0.266 (−0.953, 0.089)
bl_community_id30		−0.097	−0.033
		0.232 (−0.552, 0.358)	0.247 (−0.518, 0.451)
bl_community_id31		−0.022	−0.001
		0.279 (−0.570, 0.525)	0.280 (−0.549, 0.547)
bl_community_id33		−0.280	−0.258
		0.223 (−0.716, 0.156)	0.226 (−0.700, 0.185)
bl_community_id34		−0.190	−0.197
		0.207 (−0.595, 0.215)	0.211 (−0.611, 0.217)
bl_community_id35		−0.372	−0.417*
		0.254 (−0.871, 0.127)	0.247 (−0.902, 0.067)
bl_community_id36		−0.164	−0.171
		0.211 (−0.577, 0.249)	0.217 (−0.596, 0.254)
bl_community_id37		−0.158	−0.137
		0.223 (−0.595, 0.280)	0.227 (−0.582, 0.308)
bl_community_id38		−0.176	−0.136
		0.218 (−0.603, 0.252)	0.221 (−0.570, 0.297)
bl_community_id39		0.050	0.094
		0.212 (−0.366, 0.466)	0.210 (−0.318, 0.505)
bl_community_id40		−0.294	−0.187
		0.207 (−0.700, 0.112)	0.214 (−0.606, 0.232)
bl_community_id41		0.329	0.349
		0.272 (−0.205, 0.863)	0.275 (−0.190, 0.888)
bl_community_id42		−0.275	−0.321
		0.213 (−0.693, 0.142)	0.210 (−0.733, 0.090)
bl_community_id43		−0.311	−0.217
		0.205 (−0.714, 0.092)	0.209 (−0.627, 0.193)
bl_community_id44		0.185	0.183
		0.206 (−0.219, 0.590)	0.210 (−0.228, 0.595)
bl_community_id45		−0.364*	−0.393**
		0.193 (−0.742, 0.014)	0.194 (−0.774, −0.013)
bl_community_id46		0.125	0.146
		0.215 (−0.297, 0.547)	0.218 (−0.282, 0.574)
bl_community_id47		−0.101	−0.043
		0.198 (−0.490, 0.288)	0.208 (−0.452, 0.366)
bl_community_id49		−0.178	−0.081
		0.202 (−0.575, 0.218)	0.209 (−0.491, 0.329)
bl_community_id50		−0.163	−0.173
		0.227 (−0.609, 0.283)	0.219 (−0.603, 0.256)
bl_community_id51		−0.514***	−0.454**
		0.195 (−0.896, −0.132)	0.204 (−0.855, −0.053)
bl_community_id52		−0.139	−0.117
		0.191 (−0.514, 0.235)	0.196 (−0.502, 0.267)
bl_community_id53		−0.517***	−0.486**
		0.199 (−0.906, −0.127)	0.203 (−0.883, −0.089)
bl_community_id54		−0.225	−0.220
		0.191 (−0.601, 0.150)	0.195 (−0.602, 0.162)
bl_community_id55		−0.279	−0.294
		0.205 (−0.682, 0.123)	0.211 (−0.708, 0.120)
bl_community_id56		−0.018	−0.072
		0.230 (−0.470, 0.434)	0.240 (−0.543, 0.400)
bl_community_id57		−0.543***	−0.501**
		0.193 (−0.921, −0.164)	0.200 (−0.893, −0.110)
bl_community_id58		−0.309*	−0.310*
		0.162 (−0.626, 0.008)	0.164 (−0.631, 0.012)
bl_community_id59		−0.254**	−0.288**
		0.114 (−0.477, −0.031)	0.119 (−0.521, −0.055)
bl_community_id60		−0.241	−0.271*
		0.147 (−0.528, 0.047)	0.154 (−0.572, 0.031)
bl_community_id61		0.036	0.046
		0.125 (−0.209, 0.281)	0.128 (−0.204, 0.296)
bl_community_id62		−0.103	−0.140
		0.132 (−0.362, 0.155)	0.137 (−0.408, 0.128)
bl_community_id63		0.334**	0.336**
		0.139 (0.062, 0.607)	0.142 (0.058, 0.613)
bl_community_id64		0.016	−0.022
		0.138 (−0.255, 0.287)	0.144 (−0.305, 0.261)
bl_community_id65		−0.193	−0.217
		0.224 (−0.632, 0.245)	0.221 (−0.650, 0.216)
bl_community_id66		−0.122	−0.143
		0.151 (−0.418, 0.174)	0.160 (−0.457, 0.170)
bl_community_id68		−0.496***	−0.533***
		0.133 (−0.756, −0.236)	0.136 (−0.799, −0.266)
bl_community_id69		−0.592**	−0.573**
		0.245 (−1.073, −0.112)	0.239 (−1.041, −0.105)
bl_community_id70		−0.596***	−0.681***
		0.120 (−0.832, −0.360)	0.122 (−0.920, −0.441)
bl_community_id71		−0.309**	−0.316**
		0.125 (−0.554, −0.064)	0.125 (−0.561, −0.071)
bl_community_id72		−0.162	−0.156
		0.130 (−0.416, 0.092)	0.130 (−0.412, 0.099)
bl_community_id73		−0.104	−0.101
		0.136 (−0.371, 0.163)	0.137 (−0.369, 0.167)
bl_community_id74		0.047	0.015
		0.132 (−0.213, 0.306)	0.134 (−0.249, 0.278)
bl_community_id75		−0.348**	−0.369**
		0.155 (−0.652, −0.045)	0.154 (−0.670, −0.067)
bl_community_id76		−0.357***	−0.399***
		0.124 (−0.601, −0.114)	0.128 (−0.649, −0.149)
bl_community_id77		−0.119	−0.144
		0.124 (−0.363, 0.125)	0.127 (−0.393, 0.105)
bl_community_id78		−0.050	−0.084
		0.133 (−0.312, 0.212)	0.132 (−0.344, 0.175)
bl_community_id79		0.065	0.060
		0.129 (−0.189, 0.318)	0.131 (−0.196, 0.317)
bl_community_id80		0.366***	0.345**
		0.132 (0.108, 0.624)	0.138 (0.075, 0.615)
bl_community_id81		−0.042	−0.083
		0.144 (−0.324, 0.240)	0.143 (−0.364, 0.198)
bl_community_id82		0.063	0.037
		0.126 (−0.185, 0.310)	0.129 (−0.217, 0.291)
bl_community_id84		−0.556***	−0.537***
		0.159 (−0.868, −0.244)	0.159 (−0.849, −0.225)
bl_community_id85		−0.074	−0.022
		0.131 (−0.330, 0.182)	0.130 (−0.276, 0.233)
bl_community_id86		−0.193	−0.161
		0.144 (−0.476, 0.090)	0.142 (−0.439, 0.117)
bl_community_id87		−0.336**	−0.318**
		0.159 (−0.647, −0.025)	0.152 (−0.617, −0.019)
bl_community_id88		0.009	0.042
		0.139 (−0.262, 0.281)	0.140 (−0.233, 0.318)
bl_community_id89		−0.273*	−0.252*
		0.147 (−0.561, 0.015)	0.146 (−0.539, 0.035)
bl_community_id90		0.091	0.057
		0.191 (−0.284, 0.466)	0.203 (−0.341, 0.456)
bl_community_id91		−0.215	−0.222
		0.150 (−0.509, 0.079)	0.148 (−0.512, 0.069)
bl_community_id92		−0.230*	−0.209
		0.137 (−0.498, 0.038)	0.135 (−0.473, 0.055)
bl_community_id93		−0.505***	−0.477***
		0.127 (−0.755, −0.256)	0.125 (−0.722, −0.232)
bl_community_id94		−0.401***	−0.436***
		0.146 (−0.688, −0.114)	0.142 (−0.714, −0.157)
bl_community_id95		0.318*	0.338**
		0.163 (−0.001, 0.637)	0.163 (0.018, 0.659)
bl_community_id96		−0.627***	−0.627***
		0.166 (−0.953, −0.301)	0.175 (−0.971, −0.284)
bl_community_id97		−0.018	−0.035
		0.133 (−0.279, 0.242)	0.131 (−0.292, 0.222)
bl_community_id98		0.139	0.172
		0.170 (−0.194, 0.472)	0.168 (−0.156, 0.501)
bl_community_id99		−0.488***	−0.501***
		0.146 (−0.775, −0.200)	0.142 (−0.779, −0.222)
bl_community_id100		0.361***	0.430***
		0.136 (0.093, 0.629)	0.143 (0.149, 0.711)
bl_community_id101		−0.360**	−0.353**
		0.146 (−0.646, −0.074)	0.142 (−0.631, −0.076)
bl_community_id102		−0.291*	−0.245
		0.152 (−0.588, 0.007)	0.158 (−0.555, 0.065)
bl_community_id103		−0.013	0.070
		0.135 (−0.277, 0.252)	0.129 (−0.183, 0.323)
bl_community_id104		−0.442***	−0.409***
		0.135 (−0.707, −0.177)	0.138 (−0.681, −0.138)
bl_community_id105		−0.252	−0.223
		0.167 (−0.578, 0.075)	0.173 (−0.562, 0.115)
bl_community_id106		−0.168	−0.177
		0.183 (−0.527, 0.190)	0.182 (−0.535, 0.181)
bl_community_id107		−0.358**	−0.370**
		0.153 (−0.658, −0.058)	0.144 (−0.653, −0.087)
bl_community_id108		−0.318**	−0.302**
		0.143 (−0.597, −0.038)	0.149 (−0.595, −0.009)
bl_community_id109		−0.189	−0.203
		0.171 (−0.524, 0.147)	0.169 (−0.535, 0.129)
bl_community_id110		−0.181	−0.194
		0.125 (−0.426, 0.063)	0.124 (−0.438, 0.049)
bl_community_id111		−0.445***	−0.448***
		0.157 (−0.753, −0.137)	0.157 (−0.757, −0.140)
bl_community_id112		−0.191	−0.185
		0.127 (−0.440, 0.057)	0.125 (−0.429, 0.060)
bl_community_id113		−0.093	−0.093
		0.168 (−0.422, 0.236)	0.166 (−0.418, 0.233)
bl_community_id114		−0.259*	−0.270*
		0.153 (−0.560, 0.041)	0.149 (−0.561, 0.022)
bl_community_id115		−0.306**	−0.311**
		0.133 (−0.567, −0.044)	0.133 (−0.572, −0.050)
bl_community_id116		−0.163	−0.144
		0.116 (−0.391, 0.064)	0.113 (−0.365, 0.077)
bl_community_id117		−0.111	−0.101
		0.129 (−0.365, 0.143)	0.128 (−0.352, 0.151)
bl_census_hh_income_self_report		0.000	−0.000
		0.000 (−0.000, 0.000)	0.000 (−0.000, 0.000)
bl_loans_taken		0.004	0.004
		0.014 (−0.024, 0.032)	0.025 (−0.045, 0.053)
bl_loan_total_lent		0.000**	0.000**
		0.000 (0.000, 0.000)	0.000 (0.000, 0.000)
bl_loan_total_outstanding_99		0.000	0.000
		0.000 (−0.000, 0.000)	0.000 (−0.000, 0.000)
bl_days_worked_participant		−0.007	−0.028
		0.005 (−0.016, 0.003)	0.019 (−0.065, 0.010)
bl_cantril_present		−0.007	−0.026
		0.010 (−0.026, 0.012)	0.021 (−0.068, 0.016)
bl_phq8		0.006	0.026**
		0.004 (−0.001, 0.014)	0.011 (0.004, 0.048)
bl_gad7		0.016***	2194.675
		0.004 (0.008, 0.024)	3639.915 (−4943.243, 9332.593)
bl_pss10		0.002	0.024
		0.003 (−0.004, 0.009)	0.017 (−0.008, 0.057)
bl_pswq16		0.004*	−0.016
		0.002 (−0.000, 0.008)	0.018 (−0.051, 0.018)
bl_diener5		−0.002	−0.011
		0.002 (−0.005, 0.002)	0.010 (−0.030, 0.009)
bl_cantril_total		−0.003	0.020
		0.006 (−0.014, 0.009)	0.019 (−0.017, 0.058)
bl_mental_health_average		0.031
		0.031 (−0.030, 0.091)
bl_med_sick_accident		−0.025	−0.044
		0.035 (−0.094, 0.044)	0.152 (−0.342, 0.253)
bl_bp_tobacco		−0.129*	−0.119*
		0.068 (−0.262, 0.003)	0.070 (−0.256, 0.017)
bl_bp_systolic		0.001	0.021***
		0.001 (−0.000, 0.002)	0.008 (0.006, 0.037)
bl_shock_religious_event		−0.018	−0.022
		0.036 (−0.089, 0.053)	0.036 (−0.093, 0.050)
bl_shock_other		−0.049	−0.041
		0.102 (−0.249, 0.151)	0.106 (−0.250, 0.167)
bl_shock_costs		0.000	−0.000
		0.000 (−0.000, 0.000)	0.000 (−0.000, 0.000)
bl_participant_age		0.009***	0.019***
		0.001 (0.006, 0.011)	0.007 (0.005, 0.033)
bl_expenditure_total_nonfood_99		−0.000	−0.000
		0.000 (−0.000, 0.000)	0.000 (−0.000, 0.000)
bl_ls_owned_total		−0.000
		0.000 (−0.000, 0.000)
bl_ls_bought_total		−0.000**	0.000
		0.000 (−0.000, −0.000)	0.000 (−0.000, 0.000)
bl_ls_gift_received_total_99		0.002	−0.046**
		0.002 (−0.003, 0.006)	0.019 (−0.084, −0.008)
bl_fi_index		−0.024	0.017
		0.047 (−0.116, 0.068)	0.068 (−0.118, 0.151)
bl_fi_index_anderson		−0.033	−0.070
		0.033 (−0.098, 0.032)	0.052 (−0.173, 0.033)
bl_crop_stored_median_value		−0.000
		0.000 (−0.000, 0.000)
bl_num_incapacitated_members		0.090***	0.073
		0.033 (0.026, 0.155)	0.134 (−0.190, 0.336)
bl_incapacitated_per_capita		0.001***	0.000
		0.000 (0.000, 0.001)	0.001 (−0.002, 0.002)
bl_land_rent_value		−0.000
		0.000 (−0.000, 0.000)
bl_land_sharecrop		−0.533***	−0.517**
		0.198 (−0.922, −0.144)	0.202 (−0.914, −0.121)
bl_cash_inflow_pct_agincome		−0.002
		0.002 (−0.005, 0.001)
bl_cash_netflow_99		−0.000**	−0.000
		0.000 (−0.000, −0.000)	0.000 (−0.000, 0.000)
bl_total_consumption_99_pc		0.000	0.000
		0.000 (−0.000, 0.000)	0.000 (−0.000, 0.001)
bl_land_rent_value_MISSING		−0.586***
		0.134 (−0.849, −0.324)
bl_phq2			−0.019
			0.030 (−0.078, 0.040)
bl_pswq3			−0.022
			0.032 (−0.085, 0.041)
bl_mental_health_index			0.019
			0.037 (−0.054, 0.092)
bl_bp_diastolic			−0.030***
			0.011 (−0.051, −0.009)
bl_participant_education_years			0.004
			0.011 (−0.018, 0.026)
bl_census_hh_income_self_report_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_census_gad2_z_SQUARED			−0.011
			0.008 (−0.026, 0.005)
bl_loans_taken_SQUARED			−0.001
			0.003 (−0.007, 0.005)
bl_loan_total_lent_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_loan_total_outstanding_99_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_days_worked_participant_SQUARED			0.003
			0.002 (−0.001, 0.007)
bl_cantril_present_SQUARED			0.003
			0.003 (−0.002, 0.008)
bl_phq8_SQUARED			−0.001*
			0.001 (−0.002, 0.000)
bl_phq2_SQUARED			0.002
			0.006 (−0.009, 0.013)
bl_gad7_SQUARED			−154.240
			255.812 (−655.890, 347.411)
bl_pss10_SQUARED			−0.001
			0.000 (−0.001, 0.000)
bl_pswq3_SQUARED			0.001
			0.002 (−0.002, 0.005)
bl_pswq16_SQUARED			0.000
			0.000 (−0.000, 0.001)
bl_diener5_SQUARED			0.000
			0.000 (−0.000, 0.001)
bl_cantril_total_SQUARED			−0.001
			0.001 (−0.003, 0.001)
bl_mental_health_index_SQUARED			0.011
			0.014 (−0.018, 0.039)
bl_gad7_z_SQUARED			2489.713
			4129.289 (−5607.873, 10587.298)
bl_med_sick_accident_SQUARED			0.018
			0.047 (−0.074, 0.111)
bl_bp_systolic_SQUARED			−0.000**
			0.000 (−0.000, −0.000)
bl_bp_diastolic_SQUARED			0.000***
			0.000 (0.000, 0.000)
bl_shock_costs_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_participant_age_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_participant_education_years_SQUARED			−0.001
			0.001 (−0.003, 0.001)
bl_expenditure_total_nonfood_99_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_ls_bought_total_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_ls_gift_received_total_99_SQUARED			0.001**
			0.000 (0.000, 0.002)
bl_fi_index_SQUARED			0.023
			0.033 (−0.041, 0.087)
bl_fi_index_anderson_SQUARED			−0.017
			0.017 (−0.050, 0.016)
bl_num_incapacitated_members_SQUARED			0.010
			0.032 (−0.053, 0.074)
bl_incapacitated_per_capita_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_cash_netflow_99_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_total_consumption_99_pc_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_participant_education_years_MISSING			0.312
			1.051 (−1.749, 2.372)
Observations	12531	12531	12531

Code

```{r}
#| label: phq-lasso-square
#| warning: false
phq_grp_lasso_sq <- prep_outcome_lasso_data("phq2_z", T) %>% run_grouped_lasso_cv()

original_model <- original_regression("phq2_z")
lasso_model <- lasso_regression("phq2_z", smart_coeffs(get_grpreg_nonzero_coefs(phq_grp_lasso)))
lasso_model_sq <- lasso_regression("phq2_z", smart_coeffs(get_grpreg_nonzero_coefs(phq_grp_lasso_sq)))

models <- list(
    "Preliminary Analysis" = original_model,
    "LASSO Selected" = lasso_model,
    "LASSO Selected (w/ Squares)" = lasso_model_sq
)
makeTable(models)
```

	Preliminary Analysis	LASSO Selected	LASSO Selected (w/ Squares)
bl_phq2_z	0.079***
	0.010 (0.059, 0.100)
hh_size	0.003
	0.004 (−0.005, 0.010)
census_wealth_index	−0.018
	0.017 (−0.051, 0.015)
treatment = 1	−0.071**	−0.088***	−0.086**
	0.035 (−0.138, −0.003)	0.034 (−0.154, −0.022)	0.033 (−0.152, −0.021)
treatment = 2	−0.035	−0.058*	−0.049
	0.034 (−0.101, 0.032)	0.033 (−0.122, 0.007)	0.033 (−0.113, 0.015)
treatment = 3	−0.084***	−0.107***	−0.102***
	0.028 (−0.140, −0.028)	0.028 (−0.162, −0.053)	0.027 (−0.156, −0.049)
(Intercept)		−0.451**	−29794.524**
		0.184 (−0.811, −0.091)	12676.127 (−54652.566, −4936.482)
period1		−0.213***	−0.213***
		0.030 (−0.271, −0.155)	0.030 (−0.271, −0.155)
period2		−0.346***	−0.347***
		0.028 (−0.402, −0.291)	0.028 (−0.403, −0.292)
period3		−0.354***	−0.354***
		0.026 (−0.406, −0.302)	0.027 (−0.406, −0.302)
period4		−0.392***	−0.394***
		0.027 (−0.446, −0.339)	0.027 (−0.447, −0.340)
period5		−0.430***	−0.431***
		0.026 (−0.482, −0.379)	0.026 (−0.483, −0.379)
bl_district_id2		−0.076	−0.101
		0.149 (−0.369, 0.217)	0.159 (−0.414, 0.211)
bl_district_id3		−0.107	−0.060
		0.116 (−0.334, 0.121)	0.122 (−0.298, 0.179)
bl_district_id4		−0.091	−0.102
		0.131 (−0.348, 0.166)	0.135 (−0.366, 0.162)
bl_community_id2		−0.536***	−0.514***
		0.144 (−0.819, −0.254)	0.152 (−0.812, −0.215)
bl_community_id3		−0.099	−0.152
		0.175 (−0.442, 0.244)	0.173 (−0.491, 0.187)
bl_community_id4		−0.128	−0.077
		0.166 (−0.454, 0.198)	0.177 (−0.424, 0.269)
bl_community_id5		−0.009	−0.015
		0.178 (−0.357, 0.339)	0.186 (−0.379, 0.349)
bl_community_id6		−0.136	−0.153
		0.148 (−0.426, 0.154)	0.156 (−0.459, 0.153)
bl_community_id7		−0.492***	−0.481***
		0.120 (−0.728, −0.257)	0.127 (−0.730, −0.232)
bl_community_id8		−0.082	−0.088
		0.113 (−0.304, 0.139)	0.123 (−0.330, 0.153)
bl_community_id9		−0.216	−0.231
		0.172 (−0.554, 0.122)	0.174 (−0.572, 0.110)
bl_community_id10		−0.116	−0.027
		0.177 (−0.462, 0.231)	0.193 (−0.406, 0.351)
bl_community_id11		−0.203	−0.196
		0.153 (−0.504, 0.098)	0.152 (−0.494, 0.103)
bl_community_id12		−0.182*	−0.198*
		0.109 (−0.395, 0.031)	0.118 (−0.429, 0.034)
bl_community_id13		0.049	0.036
		0.132 (−0.209, 0.308)	0.137 (−0.232, 0.305)
bl_community_id14		0.111	0.083
		0.141 (−0.165, 0.387)	0.146 (−0.203, 0.370)
bl_community_id15		−0.108	−0.126
		0.119 (−0.341, 0.124)	0.126 (−0.373, 0.120)
bl_community_id16		−0.160	−0.206*
		0.115 (−0.386, 0.066)	0.122 (−0.445, 0.034)
bl_community_id17		−0.141	−0.138
		0.124 (−0.383, 0.101)	0.128 (−0.390, 0.113)
bl_community_id18		−0.358*	−0.353*
		0.185 (−0.720, 0.005)	0.196 (−0.738, 0.031)
bl_community_id19		0.093	0.123
		0.161 (−0.223, 0.409)	0.164 (−0.197, 0.444)
bl_community_id20		−0.268*	−0.206
		0.153 (−0.568, 0.032)	0.155 (−0.510, 0.099)
bl_community_id21		−0.092	−0.004
		0.173 (−0.432, 0.248)	0.174 (−0.345, 0.336)
bl_community_id22		0.146	0.140
		0.160 (−0.166, 0.459)	0.165 (−0.184, 0.463)
bl_community_id23		0.001	0.053
		0.163 (−0.318, 0.320)	0.171 (−0.283, 0.390)
bl_community_id24		−0.211	−0.203
		0.160 (−0.525, 0.102)	0.162 (−0.520, 0.115)
bl_community_id25		−0.267	−0.270
		0.174 (−0.608, 0.074)	0.175 (−0.614, 0.074)
bl_community_id26		−0.036	0.024
		0.187 (−0.404, 0.331)	0.192 (−0.353, 0.400)
bl_community_id27		−0.034	0.015
		0.188 (−0.403, 0.335)	0.186 (−0.350, 0.379)
bl_community_id28		−0.316**	−0.309*
		0.155 (−0.620, −0.011)	0.161 (−0.625, 0.007)
bl_community_id29		−0.307*	−0.287
		0.186 (−0.673, 0.059)	0.186 (−0.652, 0.077)
bl_community_id30		0.060	0.134
		0.178 (−0.289, 0.409)	0.188 (−0.234, 0.502)
bl_community_id31		0.002	0.031
		0.203 (−0.397, 0.400)	0.200 (−0.361, 0.422)
bl_community_id33		−0.204	−0.164
		0.207 (−0.609, 0.202)	0.210 (−0.575, 0.247)
bl_community_id34		−0.074	−0.051
		0.161 (−0.391, 0.242)	0.163 (−0.371, 0.269)
bl_community_id35		−0.388**	−0.371**
		0.192 (−0.764, −0.011)	0.186 (−0.736, −0.006)
bl_community_id36		0.015	0.036
		0.167 (−0.313, 0.343)	0.170 (−0.297, 0.369)
bl_community_id37		−0.175	−0.149
		0.164 (−0.497, 0.146)	0.164 (−0.470, 0.173)
bl_community_id38		−0.161	−0.086
		0.148 (−0.451, 0.129)	0.153 (−0.387, 0.215)
bl_community_id39		−0.333**	−0.291**
		0.139 (−0.606, −0.060)	0.141 (−0.567, −0.014)
bl_community_id40		−0.195	−0.123
		0.164 (−0.517, 0.128)	0.166 (−0.449, 0.202)
bl_community_id41		0.373*	0.440*
		0.222 (−0.062, 0.807)	0.229 (−0.010, 0.890)
bl_community_id42		−0.064	−0.036
		0.157 (−0.371, 0.244)	0.157 (−0.344, 0.273)
bl_community_id43		−0.262	−0.129
		0.171 (−0.597, 0.073)	0.172 (−0.466, 0.208)
bl_community_id44		0.070	0.077
		0.144 (−0.213, 0.354)	0.145 (−0.208, 0.362)
bl_community_id45		−0.221	−0.225
		0.150 (−0.514, 0.073)	0.151 (−0.521, 0.072)
bl_community_id46		0.008	0.036
		0.141 (−0.269, 0.285)	0.140 (−0.238, 0.310)
bl_community_id47		−0.083	0.051
		0.159 (−0.394, 0.228)	0.147 (−0.237, 0.339)
bl_community_id49		−0.220	−0.137
		0.195 (−0.602, 0.161)	0.197 (−0.523, 0.250)
bl_community_id50		−0.118	−0.121
		0.161 (−0.434, 0.199)	0.162 (−0.439, 0.196)
bl_community_id51		−0.315**	−0.252
		0.149 (−0.607, −0.024)	0.159 (−0.564, 0.060)
bl_community_id52		−0.134	−0.142
		0.145 (−0.419, 0.151)	0.146 (−0.428, 0.145)
bl_community_id53		−0.230	−0.188
		0.154 (−0.532, 0.073)	0.156 (−0.495, 0.118)
bl_community_id54		−0.141	−0.096
		0.140 (−0.415, 0.134)	0.142 (−0.375, 0.183)
bl_community_id55		−0.266*	−0.256*
		0.141 (−0.542, 0.010)	0.144 (−0.539, 0.027)
bl_community_id56		0.132	0.162
		0.164 (−0.189, 0.453)	0.169 (−0.170, 0.495)
bl_community_id57		−0.376***	−0.331**
		0.144 (−0.658, −0.094)	0.148 (−0.621, −0.041)
bl_community_id58		−0.106	−0.150
		0.164 (−0.428, 0.217)	0.168 (−0.479, 0.178)
bl_community_id59		−0.097	−0.071
		0.121 (−0.333, 0.140)	0.118 (−0.303, 0.160)
bl_community_id60		0.119	0.058
		0.152 (−0.180, 0.418)	0.153 (−0.242, 0.358)
bl_community_id61		0.088	−0.009
		0.107 (−0.122, 0.297)	0.108 (−0.221, 0.203)
bl_community_id62		0.266**	0.197
		0.125 (0.021, 0.511)	0.125 (−0.048, 0.443)
bl_community_id63		0.026	−0.053
		0.161 (−0.289, 0.342)	0.156 (−0.359, 0.253)
bl_community_id64		0.198	0.138
		0.129 (−0.054, 0.451)	0.129 (−0.115, 0.392)
bl_community_id65		−0.140	−0.201
		0.174 (−0.482, 0.201)	0.177 (−0.549, 0.147)
bl_community_id66		0.079	−0.070
		0.148 (−0.211, 0.369)	0.153 (−0.370, 0.231)
bl_community_id68		−0.406***	−0.445***
		0.117 (−0.634, −0.177)	0.116 (−0.673, −0.218)
bl_community_id69		−0.508***	−0.494***
		0.157 (−0.816, −0.199)	0.150 (−0.789, −0.200)
bl_community_id70		−0.311***	−0.369***
		0.118 (−0.542, −0.079)	0.123 (−0.609, −0.128)
bl_community_id71		−0.030	0.003
		0.105 (−0.236, 0.175)	0.104 (−0.202, 0.208)
bl_community_id72		0.122	0.133
		0.114 (−0.101, 0.346)	0.107 (−0.077, 0.343)
bl_community_id73		0.025	−0.005
		0.113 (−0.197, 0.247)	0.119 (−0.239, 0.229)
bl_community_id74		0.198*	0.182*
		0.107 (−0.011, 0.408)	0.109 (−0.032, 0.395)
bl_community_id75		−0.198	−0.228
		0.142 (−0.477, 0.081)	0.140 (−0.502, 0.046)
bl_community_id76		−0.218**	−0.290***
		0.099 (−0.411, −0.024)	0.100 (−0.487, −0.094)
bl_community_id77		0.032	0.042
		0.121 (−0.206, 0.270)	0.120 (−0.193, 0.277)
bl_community_id78		0.082	0.060
		0.105 (−0.124, 0.287)	0.102 (−0.140, 0.260)
bl_community_id79		0.063	0.036
		0.090 (−0.114, 0.239)	0.087 (−0.134, 0.206)
bl_community_id80		0.361***	0.304***
		0.103 (0.160, 0.562)	0.105 (0.099, 0.510)
bl_community_id81		−0.107	−0.184
		0.122 (−0.345, 0.132)	0.120 (−0.420, 0.052)
bl_community_id82		−0.024	−0.087
		0.103 (−0.225, 0.178)	0.102 (−0.287, 0.113)
bl_community_id84		−0.439***	−0.393***
		0.138 (−0.710, −0.167)	0.153 (−0.693, −0.094)
bl_community_id85		−0.124	−0.071
		0.141 (−0.401, 0.154)	0.141 (−0.348, 0.206)
bl_community_id86		−0.127	−0.093
		0.160 (−0.441, 0.186)	0.161 (−0.409, 0.223)
bl_community_id87		−0.335*	−0.353**
		0.178 (−0.684, 0.015)	0.167 (−0.680, −0.026)
bl_community_id88		−0.132	−0.143
		0.130 (−0.387, 0.124)	0.128 (−0.393, 0.107)
bl_community_id89		−0.172	−0.160
		0.144 (−0.454, 0.110)	0.141 (−0.437, 0.116)
bl_community_id90		0.126	0.115
		0.119 (−0.107, 0.358)	0.125 (−0.131, 0.361)
bl_community_id91		−0.121	−0.092
		0.158 (−0.431, 0.188)	0.162 (−0.409, 0.225)
bl_community_id92		−0.163	−0.168
		0.125 (−0.408, 0.082)	0.125 (−0.413, 0.077)
bl_community_id93		−0.311**	−0.303**
		0.130 (−0.566, −0.056)	0.128 (−0.553, −0.053)
bl_community_id94		−0.482***	−0.542***
		0.175 (−0.825, −0.138)	0.154 (−0.844, −0.241)
bl_community_id95		0.304*	0.308*
		0.173 (−0.036, 0.643)	0.167 (−0.019, 0.636)
bl_community_id96		−0.346**	−0.355**
		0.150 (−0.640, −0.053)	0.151 (−0.651, −0.058)
bl_community_id97		0.074	0.055
		0.131 (−0.183, 0.332)	0.123 (−0.186, 0.297)
bl_community_id98		−0.052	−0.022
		0.153 (−0.351, 0.247)	0.152 (−0.321, 0.277)
bl_community_id99		−0.131	−0.119
		0.141 (−0.408, 0.145)	0.136 (−0.385, 0.148)
bl_community_id100		0.335*	0.377**
		0.187 (−0.032, 0.701)	0.185 (0.014, 0.740)
bl_community_id101		−0.392***	−0.379***
		0.123 (−0.634, −0.150)	0.122 (−0.618, −0.140)
bl_community_id102		−0.221	−0.190
		0.143 (−0.500, 0.059)	0.145 (−0.475, 0.095)
bl_community_id103		0.042	0.062
		0.131 (−0.215, 0.300)	0.124 (−0.181, 0.306)
bl_community_id104		−0.416***	−0.385***
		0.131 (−0.674, −0.158)	0.134 (−0.648, −0.122)
bl_community_id105		−0.280*	−0.271*
		0.148 (−0.569, 0.010)	0.149 (−0.563, 0.020)
bl_community_id106		−0.116	−0.123
		0.215 (−0.539, 0.306)	0.214 (−0.544, 0.297)
bl_community_id107		−0.221	−0.212
		0.137 (−0.490, 0.047)	0.134 (−0.475, 0.051)
bl_community_id108		−0.114	−0.122
		0.130 (−0.368, 0.140)	0.126 (−0.369, 0.125)
bl_community_id109		0.001	−0.012
		0.128 (−0.249, 0.251)	0.124 (−0.255, 0.232)
bl_community_id110		−0.109	−0.090
		0.133 (−0.369, 0.151)	0.131 (−0.347, 0.167)
bl_community_id111		−0.415***	−0.400***
		0.133 (−0.676, −0.155)	0.135 (−0.664, −0.135)
bl_community_id112		−0.097	−0.125
		0.128 (−0.348, 0.154)	0.129 (−0.378, 0.128)
bl_community_id113		−0.026	−0.030
		0.157 (−0.333, 0.281)	0.153 (−0.330, 0.271)
bl_community_id114		−0.194	−0.207
		0.145 (−0.478, 0.089)	0.139 (−0.481, 0.066)
bl_community_id115		−0.166	−0.150
		0.129 (−0.420, 0.088)	0.127 (−0.399, 0.098)
bl_community_id116		−0.167	−0.148
		0.108 (−0.379, 0.044)	0.103 (−0.350, 0.053)
bl_community_id117		−0.053	−0.056
		0.123 (−0.293, 0.188)	0.123 (−0.296, 0.185)
bl_cohort2		0.018	0.028
		0.026 (−0.034, 0.070)	0.026 (−0.023, 0.080)
bl_census_hh_income_self_report		0.000	−0.000
		0.000 (−0.000, 0.000)	0.000 (−0.000, 0.000)
bl_loans_taken		0.015	0.029
		0.013 (−0.010, 0.040)	0.023 (−0.017, 0.075)
bl_loan_total_payment		0.000***	0.000*
		0.000 (0.000, 0.000)	0.000 (−0.000, 0.000)
bl_loan_total_lent		0.000***	0.000
		0.000 (0.000, 0.000)	0.000 (−0.000, 0.000)
bl_loan_total_outstanding_99		0.000	−0.000
		0.000 (−0.000, 0.000)	0.000 (−0.000, 0.000)
bl_food_purchase_total_phone		0.000
		0.000 (−0.000, 0.000)
bl_days_worked_participant		−0.008*	−0.019
		0.005 (−0.017, 0.001)	0.017 (−0.053, 0.014)
bl_cantril_present		−0.006	−0.005
		0.005 (−0.015, 0.003)	0.016 (−0.037, 0.026)
bl_phq2		0.021*	0.056**
		0.011 (−0.002, 0.043)	0.024 (0.010, 0.103)
bl_gad7		0.019***	8375.784**
		0.004 (0.012, 0.027)	3563.498 (1387.720, 15363.847)
bl_pss10		0.005	−0.000
		0.003 (−0.001, 0.010)	0.013 (−0.026, 0.025)
bl_pswq16		0.005**	−0.017
		0.002 (0.001, 0.008)	0.014 (−0.045, 0.011)
bl_diener5		−0.001	0.002
		0.002 (−0.005, 0.002)	0.010 (−0.017, 0.021)
bl_mental_health_average		−0.021
		0.035 (−0.090, 0.049)
bl_med_sick_accident		0.007	−0.031
		0.032 (−0.057, 0.071)	0.144 (−0.314, 0.252)
bl_shock_costs		0.000**	−0.000
		0.000 (0.000, 0.000)	0.000 (−0.000, 0.000)
bl_participant_age		0.008***	0.022***
		0.001 (0.005, 0.010)	0.007 (0.008, 0.036)
bl_share_elderly		−0.299	−0.303
		0.187 (−0.665, 0.067)	0.408 (−1.103, 0.496)
bl_ls_bought_total_99		0.001	0.005*
		0.000 (−0.000, 0.001)	0.003 (−0.001, 0.011)
bl_dg_buy_total_value		−0.000***
		0.000 (−0.000, −0.000)
bl_fi_index		−0.004	0.096
		0.045 (−0.092, 0.084)	0.067 (−0.035, 0.227)
bl_fi_index_anderson		−0.050	−0.136***
		0.031 (−0.111, 0.012)	0.051 (−0.235, −0.036)
bl_expenditure_total_food_99		−0.000
		0.000 (−0.000, 0.000)
bl_num_incapacitated_members		0.044	0.091
		0.030 (−0.014, 0.103)	0.130 (−0.163, 0.345)
bl_land_rent_value		−0.000	0.000
		0.000 (−0.000, 0.000)	0.000 (−0.001, 0.001)
bl_land_own_farm_value		0.000	−0.000
		0.000 (−0.000, 0.000)	0.000 (−0.000, 0.000)
bl_cash_outflow_99		−0.000
		0.000 (−0.000, 0.000)
bl_cash_outflow_pct_agequipment		0.004	0.010
		0.004 (−0.003, 0.011)	0.006 (−0.002, 0.023)
bl_cash_outflow_pct_lent		−0.007***	−0.003
		0.003 (−0.013, −0.002)	0.005 (−0.013, 0.007)
bl_cash_netflow_99		−0.000*	−0.000
		0.000 (−0.000, 0.000)	0.000 (−0.000, 0.000)
bl_land_rent_value_MISSING		−0.529**	−0.505**
		0.248 (−1.015, −0.043)	0.245 (−0.987, −0.024)
bl_loan_total_outstanding			0.000
			0.000 (−0.000, 0.000)
bl_shock_death_relative			0.049**
			0.023 (0.003, 0.095)
bl_participant_education_years			−0.012
			0.010 (−0.032, 0.007)
bl_max_education_level			0.008
			0.012 (−0.014, 0.031)
bl_ls_sold_total			0.000
			0.000 (−0.000, 0.000)
bl_ag_eqp_sale_total_value			−0.001
			0.002 (−0.006, 0.003)
bl_asset_purchases			−0.000
			0.000 (−0.000, 0.000)
bl_cash_inflow_pct_gifts			0.005**
			0.002 (0.000, 0.009)
bl_cash_outflow_pct_durables			0.001
			0.005 (−0.009, 0.011)
bl_census_hh_income_self_report_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_census_gad2_z_SQUARED			−0.017**
			0.007 (−0.031, −0.002)
bl_census_phq2_z_SQUARED			0.009
			0.008 (−0.008, 0.025)
bl_loans_taken_SQUARED			−0.004
			0.003 (−0.009, 0.001)
bl_loan_total_outstanding_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_loan_total_payment_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_loan_total_lent_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_loan_total_outstanding_99_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_days_worked_participant_SQUARED			0.001
			0.002 (−0.003, 0.005)
bl_cantril_present_SQUARED			−0.000
			0.002 (−0.003, 0.003)
bl_phq2_SQUARED			−0.008
			0.005 (−0.017, 0.002)
bl_gad7_SQUARED			−588.646**
			250.441 (−1079.764, −97.527)
bl_pss10_SQUARED			0.000
			0.000 (−0.001, 0.001)
bl_pswq16_SQUARED			0.000
			0.000 (−0.000, 0.001)
bl_diener5_SQUARED			−0.000
			0.000 (−0.001, 0.000)
bl_phq8_z_SQUARED			−0.012
			0.010 (−0.032, 0.007)
bl_gad7_z_SQUARED			9501.844**
			4042.597 (1574.261, 17429.428)
bl_med_sick_accident_SQUARED			0.004
			0.044 (−0.083, 0.091)
bl_shock_costs_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_participant_age_SQUARED			−0.000*
			0.000 (−0.000, 0.000)
bl_participant_education_years_SQUARED			0.000
			0.001 (−0.001, 0.002)
bl_max_education_level_SQUARED			−0.000
			0.001 (−0.002, 0.002)
bl_share_elderly_SQUARED			0.076
			1.533 (−2.930, 3.083)
bl_ls_sold_total_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_ls_bought_total_99_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_ag_eqp_sale_total_value_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_ag_eqp_sale_total_value_99_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_fi_index_SQUARED			0.069**
			0.032 (0.007, 0.131)
bl_fi_index_anderson_SQUARED			−0.041**
			0.016 (−0.072, −0.009)
bl_num_incapacitated_members_SQUARED			−0.018
			0.033 (−0.083, 0.046)
bl_land_rent_value_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_land_own_farm_value_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_asset_purchases_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_cash_inflow_pct_gifts_SQUARED			−0.000**
			0.000 (−0.000, −0.000)
bl_cash_outflow_pct_durables_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_cash_outflow_pct_agequipment_SQUARED			−0.000
			0.000 (−0.001, 0.000)
bl_cash_outflow_pct_lent_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_cash_netflow_99_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_participant_education_years_MISSING			−1.189
			0.917 (−2.987, 0.609)
Observations	12531	12531	12531

Code

```{r}
#| label: income-regression-square
#| warning: false
income_grp_lasso_sq <- run_grouped_lasso_cv(prep_outcome_lasso_data("total_income_99", T))

original_model <- original_regression("total_income_99")
lasso_model <- lasso_regression("total_income_99", smart_coeffs(get_grpreg_nonzero_coefs(income_grp_lasso)))
lasso_model_sq <- lasso_regression("total_income_99", smart_coeffs(get_grpreg_nonzero_coefs(income_grp_lasso_sq)))

models <- list(
    "Preliminary Analysis" = original_model,
    "LASSO Selected" = lasso_model,
    "LASSO Selected (w/ Squares)" = lasso_model_sq
)
makeTable(models)
```

	Preliminary Analysis	LASSO Selected	LASSO Selected (w/ Squares)
bl_total_income_99	0.035***		−0.082
	0.008 (0.019, 0.051)		0.391 (−0.849, 0.685)
hh_size	3.076*
	1.714 (−0.285, 6.437)
census_wealth_index	35.963***
	7.996 (20.283, 51.643)
treatment = 1	−25.115*	−14.684	−15.771
	15.008 (−54.545, 4.316)	14.995 (−44.089, 14.721)	306.830 (−617.467, 585.925)
treatment = 2	18.379	17.304	14.998
	16.462 (−13.903, 50.661)	16.496 (−15.045, 49.654)	310.087 (−593.086, 623.082)
treatment = 3	−10.901	−10.041	−9.664
	13.109 (−36.609, 14.806)	13.412 (−36.341, 16.259)	240.380 (−481.053, 461.724)
(Intercept)		256.255***	−274.829
		34.052 (189.479, 323.030)	3137.799 (−6428.088, 5878.430)
period1		−140.122***	−147.837**
		14.504 (−168.564, −111.680)	58.708 (−262.963, −32.710)
period2		−159.311***	−162.457***
		13.500 (−185.783, −132.838)	33.129 (−227.423, −97.491)
period3		−176.988***	−179.661***
		13.032 (−202.544, −151.432)	24.923 (−228.536, −130.786)
period4		−164.894***	−166.017***
		13.015 (−190.417, −139.370)	20.276 (−205.778, −126.255)
period5		−163.009***	−165.237***
		13.054 (−188.607, −137.410)	30.543 (−225.132, −105.342)
bl_district_id2		−116.040***	−115.559
		18.950 (−153.201, −78.879)	386.050 (−872.607, 641.489)
bl_district_id3		−71.094***	−83.736
		21.452 (−113.162, −29.026)	447.143 (−960.588, 793.116)
bl_district_id4		−93.583***	−99.910
		19.075 (−130.989, −56.177)	384.183 (−853.298, 653.478)
bl_wave2		40.160***	41.346
		9.323 (21.876, 58.443)	203.310 (−357.347, 440.038)
bl_census_hh_income_self_report		0.005
		0.013 (−0.020, 0.030)
bl_census_wealth_index		24.501***	24.776
		7.979 (8.855, 40.147)	168.889 (−306.417, 355.968)
bl_census_hh_income_self_report_99		0.004	−0.018
		0.016 (−0.028, 0.036)	0.230 (−0.468, 0.433)
bl_loan_total_lent		0.053**	0.002
		0.026 (0.002, 0.105)	1.044 (−2.046, 2.050)
bl_food_purchase_total_bl		0.022
		0.017 (−0.010, 0.055)
bl_diener5		0.648	8.780
		1.679 (−2.644, 3.940)	133.662 (−253.333, 270.892)
bl_diener3		1.320	−1.326
		2.393 (−3.373, 6.013)	170.209 (−335.109, 332.456)
bl_mental_health_average		21.526***
		6.478 (8.823, 34.229)
bl_med_assistance_received		13.508	13.183
		11.866 (−9.761, 36.778)	257.306 (−491.397, 517.763)
bl_shock_death_livestock		14.621	12.921
		10.036 (−5.059, 34.301)	228.413 (−435.000, 460.842)
bl_shock_religious_event		23.559**	25.883
		11.301 (1.399, 45.720)	227.977 (−421.182, 472.948)
bl_num_adults		9.420**	44.888
		4.390 (0.811, 18.029)	606.546 (−1144.556, 1234.332)
bl_avg_education_years		−3.989*	−10.696
		2.157 (−8.219, 0.241)	118.110 (−242.312, 220.920)
bl_expenditure_total_nonfood_99		0.007	−0.043
		0.027 (−0.045, 0.059)	1.180 (−2.357, 2.271)
bl_dg_own_total_value_99		0.002***	0.003
		0.001 (0.000, 0.003)	0.033 (−0.062, 0.068)
bl_svg_current_savings		0.009	0.004
		0.007 (−0.005, 0.023)	0.458 (−0.894, 0.902)
bl_svg_withdrawals_99		0.025	0.162
		0.044 (−0.061, 0.111)	3.964 (−7.610, 7.935)
bl_total_consumption_99		0.012	0.135
		0.019 (−0.025, 0.050)	1.948 (−3.685, 3.955)
bl_cash_inflow_99		−0.010
		0.009 (−0.027, 0.007)
bl_cash_inflow_pct_cropsale		0.408	−0.289
		0.268 (−0.117, 0.933)	50.199 (−98.730, 98.152)
bl_cash_inflow_pct_agincome		1.376	−1.573
		1.054 (−0.690, 3.442)	43.253 (−86.394, 83.247)
bl_cash_inflow_pct_gifts		0.875**	−0.335
		0.350 (0.189, 1.562)	12.515 (−24.876, 24.207)
bl_cash_outflow_99		0.002	−0.066
		0.016 (−0.029, 0.032)	1.758 (−3.513, 3.380)
bl_total_income_99_pc		0.245**	0.994
		0.105 (0.039, 0.451)	17.030 (−32.402, 34.391)
on_time			−23.522
			110.674 (−240.555, 193.512)
bl_gad2			2.996
			193.835 (−377.116, 383.108)
bl_pss10			9.776
			118.001 (−221.626, 241.177)
bl_pswq3			−3.766
			248.800 (−491.665, 484.133)
bl_pswq16			8.566
			121.065 (−228.844, 245.976)
bl_shock_accident_injury			15.176
			228.831 (−433.565, 463.916)
bl_adult_equivalent			−4.167
			602.206 (−1185.100, 1176.765)
bl_ls_owned_total			−0.000
			0.019 (−0.037, 0.036)
bl_dg_buy_total_value_99			−0.187
			4.454 (−8.922, 8.548)
bl_ag_eqp_sale_total_value			1.648
			5.181 (−8.513, 11.808)
bl_dd_hdds			17.659
			129.414 (−236.125, 271.442)
bl_expenditure_total_food			0.020
			0.282 (−0.532, 0.572)
bl_total_income_99_w_study			−0.336
			2.659 (−5.550, 4.878)
bl_cash_inflow_pct_debt			−57.088
			384.260 (−810.625, 696.449)
bl_census_wealth_index_SQUARED			8.652
			227.575 (−437.625, 454.929)
bl_census_gad2_z_SQUARED			7.231
			78.631 (−146.965, 161.427)
bl_census_hh_income_self_report_99_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_loan_total_lent_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_gad2_SQUARED			0.572
			38.976 (−75.861, 77.005)
bl_pss10_SQUARED			−0.195
			2.878 (−5.838, 5.448)
bl_pswq3_SQUARED			0.278
			13.171 (−25.550, 26.106)
bl_pswq16_SQUARED			−0.076
			1.201 (−2.433, 2.280)
bl_diener5_SQUARED			−0.196
			3.348 (−6.761, 6.369)
bl_diener3_SQUARED			0.099
			7.449 (−14.507, 14.706)
bl_num_adults_SQUARED			−5.594
			88.427 (−179.000, 167.811)
bl_adult_equivalent_SQUARED			1.836
			70.511 (−136.438, 140.110)
bl_avg_education_years_SQUARED			0.894
			14.452 (−27.446, 29.233)
bl_expenditure_total_nonfood_99_SQUARED			0.000
			0.001 (−0.002, 0.002)
bl_ls_owned_total_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_dg_own_total_value_99_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_dg_buy_total_value_99_SQUARED			0.000
			0.006 (−0.012, 0.013)
bl_ag_eqp_sale_total_value_SQUARED			−0.004
			0.019 (−0.042, 0.033)
bl_dd_hdds_SQUARED			−1.057
			11.613 (−23.830, 21.716)
bl_expenditure_total_food_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_svg_current_savings_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_svg_withdrawals_99_SQUARED			−0.000
			0.009 (−0.018, 0.017)
bl_total_income_99_SQUARED			−0.000
			0.003 (−0.006, 0.005)
bl_total_income_99_w_study_SQUARED			−0.002
			0.007 (−0.016, 0.012)
bl_total_consumption_99_SQUARED			−0.000
			0.000 (−0.001, 0.001)
bl_cash_inflow_pct_cropsale_SQUARED			0.007
			0.555 (−1.081, 1.096)
bl_cash_inflow_pct_agincome_SQUARED			0.033
			0.445 (−0.839, 0.905)
bl_cash_inflow_pct_gifts_SQUARED			0.013
			0.131 (−0.243, 0.270)
bl_cash_inflow_pct_debt_SQUARED			5.138
			25.462 (−44.793, 55.070)
bl_cash_outflow_99_SQUARED			0.000
			0.000 (−0.001, 0.001)
bl_total_income_99_pc_SQUARED			−0.001
			0.028 (−0.056, 0.054)
bl_expenditure_total_food_MISSING			−152.209
			1070.046 (−2250.581, 1946.164)
Observations	12593	12593	12593

Code

```{r}
#| label: consumption-regression-square
#| warning: false
cons_grp_lasso_sq <- run_grouped_lasso_cv(prep_outcome_lasso_data("total_consumption_99", T))

original_model <- original_regression("total_consumption_99")
lasso_model <- lasso_regression("total_consumption_99", smart_coeffs(get_grpreg_nonzero_coefs(cons_grp_lasso)))
lasso_model_sq <- lasso_regression("total_consumption_99", smart_coeffs(get_grpreg_nonzero_coefs(cons_grp_lasso_sq)))

models <- list(
    "Preliminary Analysis" = original_model,
    "LASSO Selected" = lasso_model,
    "LASSO Selected (w/ Squares)" = lasso_model_sq
)
makeTable(models)
```

	Preliminary Analysis	LASSO Selected	LASSO Selected (w/ Squares)
bl_total_consumption_99	0.142***	0.036	0.084
	0.009 (0.124, 0.160)	0.073 (−0.106, 0.179)	0.072 (−0.058, 0.226)
hh_size	13.560***
	2.277 (9.095, 18.024)
census_wealth_index	24.902**
	9.782 (5.719, 44.084)
treatment = 1	71.600***	59.816***	61.277***
	19.322 (33.709, 109.492)	17.942 (24.632, 95.001)	17.784 (26.402, 96.152)
treatment = 2	72.977***	47.744**	54.064***
	18.825 (36.062, 109.893)	18.676 (11.121, 84.367)	18.528 (17.731, 90.398)
treatment = 3	65.175***	44.139***	45.026***
	15.447 (34.884, 95.467)	14.604 (15.501, 72.777)	14.462 (16.666, 73.385)
(Intercept)		258.351***	206.945
		95.576 (70.925, 445.777)	149.502 (−86.230, 500.121)
period1		−57.237***	−57.223***
		16.568 (−89.727, −24.747)	16.600 (−89.776, −24.669)
period2		−269.336***	−269.631***
		14.579 (−297.927, −240.746)	14.613 (−298.286, −240.975)
period3		−339.840***	−340.202***
		13.961 (−367.218, −312.462)	13.981 (−367.619, −312.785)
period4		−394.072***	−394.509***
		13.585 (−420.712, −367.431)	13.608 (−421.194, −367.825)
period5		−424.560***	−424.730***
		13.611 (−451.251, −397.869)	13.625 (−451.448, −398.011)
on_time		16.943*	16.514*
		8.664 (−0.047, 33.932)	8.580 (−0.312, 33.340)
bl_district_id2		17.239	−14.101
		85.887 (−151.186, 185.664)	86.871 (−184.455, 156.254)
bl_district_id3		103.700	74.519
		84.730 (−62.456, 269.856)	84.874 (−91.920, 240.958)
bl_district_id4		108.021	85.350
		84.839 (−58.350, 274.391)	85.428 (−82.176, 252.876)
bl_community_id2		168.946*	162.303
		100.827 (−28.776, 366.668)	102.289 (−38.287, 362.894)
bl_community_id3		−14.720	−49.070
		111.623 (−233.614, 204.174)	110.830 (−266.410, 168.270)
bl_community_id4		120.355	103.021
		116.004 (−107.129, 347.840)	110.510 (−113.689, 319.732)
bl_community_id5		75.168	54.642
		91.979 (−105.203, 255.539)	93.772 (−129.246, 238.530)
bl_community_id6		82.793	34.385
		108.966 (−130.891, 296.476)	110.699 (−182.697, 251.468)
bl_community_id7		−72.942	−90.305
		101.456 (−271.898, 126.014)	107.051 (−300.234, 119.624)
bl_community_id8		−75.452	−89.646
		83.360 (−238.922, 88.019)	83.837 (−254.051, 74.760)
bl_community_id9		341.555*	311.582
		199.208 (−49.094, 732.203)	192.075 (−65.079, 688.244)
bl_community_id10		194.019	143.790
		127.751 (−56.502, 444.539)	131.353 (−113.795, 401.375)
bl_community_id11		181.533**	150.247*
		88.674 (7.643, 355.424)	88.063 (−22.446, 322.940)
bl_community_id12		68.273	58.313
		85.985 (−100.344, 236.891)	87.718 (−113.703, 230.329)
bl_community_id13		175.193*	151.650
		101.684 (−24.211, 374.597)	102.412 (−49.182, 352.481)
bl_community_id14		−58.239	−80.683
		96.017 (−246.530, 130.052)	96.380 (−269.685, 108.319)
bl_community_id15		164.962*	153.141
		95.625 (−22.560, 352.484)	94.264 (−31.712, 337.995)
bl_community_id16		189.798**	159.010*
		89.247 (14.784, 364.812)	88.167 (−13.885, 331.906)
bl_community_id17		19.782	10.326
		84.566 (−146.053, 185.616)	84.516 (−155.412, 176.063)
bl_community_id18		8.567	44.402
		80.671 (−149.629, 166.763)	79.045 (−110.606, 199.411)
bl_community_id19		−15.252	−11.035
		71.070 (−154.621, 124.117)	74.594 (−157.314, 135.244)
bl_community_id20		1.635	14.455
		83.458 (−162.027, 165.297)	79.003 (−140.470, 169.381)
bl_community_id21		24.810	58.315
		53.817 (−80.725, 130.345)	59.277 (−57.928, 174.557)
bl_community_id22		61.317	34.125
		97.654 (−130.183, 252.818)	96.585 (−155.280, 223.530)
bl_community_id23		−2.560	43.841
		93.647 (−186.204, 181.084)	92.818 (−138.176, 225.858)
bl_community_id24		15.357	18.233
		59.141 (−100.620, 131.334)	63.377 (−106.051, 142.517)
bl_community_id25		210.242*	211.484*
		115.200 (−15.667, 436.150)	113.840 (−11.757, 434.726)
bl_community_id26		120.197	127.993
		76.301 (−29.429, 269.824)	80.917 (−30.685, 286.672)
bl_community_id27		19.093	24.190
		134.054 (−243.789, 281.975)	132.992 (−236.608, 284.989)
bl_community_id28		−29.167	−14.347
		56.445 (−139.855, 81.522)	56.512 (−125.168, 96.473)
bl_community_id29		−72.955	−67.202
		73.672 (−217.426, 71.517)	74.608 (−213.509, 79.105)
bl_community_id30		123.659*	139.991**
		66.181 (−6.123, 253.441)	66.771 (9.052, 270.930)
bl_community_id31		118.503	122.870
		135.586 (−147.383, 384.390)	141.764 (−155.131, 400.872)
bl_community_id33		−82.785	−89.751
		55.962 (−192.526, 26.956)	56.091 (−199.746, 20.244)
bl_community_id34		165.615**	157.163*
		84.132 (0.631, 330.598)	83.836 (−7.241, 321.566)
bl_community_id35		−65.323	−60.225
		75.462 (−213.304, 82.658)	70.555 (−198.584, 78.133)
bl_community_id36		−28.286	−43.425
		57.752 (−141.538, 84.966)	61.320 (−163.674, 76.824)
bl_community_id37		156.873**	172.773**
		67.576 (24.355, 289.391)	67.932 (39.558, 305.988)
bl_community_id38		13.346	45.798
		59.845 (−104.012, 130.703)	62.850 (−77.451, 169.047)
bl_community_id39		18.346	36.091
		95.159 (−168.262, 204.954)	99.891 (−159.797, 231.979)
bl_community_id40		−104.145*	−87.541
		60.639 (−223.059, 14.769)	65.766 (−216.510, 41.428)
bl_community_id41		61.928	74.798
		76.704 (−88.489, 212.344)	79.880 (−81.848, 231.444)
bl_community_id42		70.743	60.772
		61.468 (−49.795, 191.282)	65.083 (−66.857, 188.402)
bl_community_id43		100.296	135.098**
		64.543 (−26.274, 226.865)	65.636 (6.384, 263.812)
bl_community_id44		−37.940	−43.634
		64.187 (−163.812, 87.932)	65.148 (−171.390, 84.122)
bl_community_id45		−23.005	−27.713
		72.602 (−165.378, 119.369)	75.566 (−175.899, 120.473)
bl_community_id46		−15.613	2.485
		64.468 (−142.035, 110.809)	65.943 (−126.830, 131.800)
bl_community_id47		69.021	87.624
		55.225 (−39.276, 177.318)	60.846 (−31.695, 206.943)
bl_community_id49		419.272***	419.898***
		142.380 (140.064, 698.481)	144.892 (135.764, 704.032)
bl_community_id50		34.227	53.494
		76.655 (−116.094, 184.548)	77.508 (−98.500, 205.488)
bl_community_id51		2.425	4.107
		69.024 (−132.932, 137.782)	68.757 (−130.726, 138.939)
bl_community_id52		29.046	32.261
		75.045 (−118.117, 176.210)	77.040 (−118.815, 183.336)
bl_community_id53		17.359	23.821
		58.799 (−97.947, 132.665)	61.627 (−97.030, 144.673)
bl_community_id54		57.426	58.424
		64.722 (−69.495, 184.347)	63.935 (−66.953, 183.801)
bl_community_id55		34.602	41.135
		63.026 (−88.993, 158.196)	64.697 (−85.737, 168.006)
bl_community_id56		78.128	63.556
		77.443 (−73.739, 229.994)	82.527 (−98.281, 225.393)
bl_community_id57		55.816	68.910
		72.398 (−86.158, 197.789)	70.544 (−69.427, 207.247)
bl_community_id58		−234.679***	−205.066***
		64.376 (−360.921, −108.436)	63.050 (−328.708, −81.423)
bl_community_id59		−251.770***	−224.265***
		57.997 (−365.503, −138.037)	59.076 (−340.113, −108.416)
bl_community_id60		−39.752	−57.042
		87.625 (−211.586, 132.082)	88.835 (−231.249, 117.164)
bl_community_id61		−69.818	−49.202
		68.573 (−204.290, 64.655)	66.716 (−180.033, 81.628)
bl_community_id62		−271.116***	−271.025***
		59.512 (−387.819, −154.413)	58.004 (−384.771, −157.279)
bl_community_id63		5.301	2.332
		70.855 (−133.646, 144.248)	76.294 (−147.281, 151.945)
bl_community_id64		−79.398	−103.278
		71.922 (−220.438, 61.641)	72.763 (−245.967, 39.410)
bl_community_id65		−33.486	−54.969
		76.649 (−183.795, 116.824)	77.160 (−206.280, 96.341)
bl_community_id66		−204.168***	−220.104***
		69.186 (−339.843, −68.494)	77.832 (−372.734, −67.474)
bl_community_id68		−104.604*	−121.095**
		58.953 (−220.212, 11.003)	58.280 (−235.383, −6.807)
bl_community_id69		−290.425***	−273.257***
		63.994 (−415.919, −164.932)	64.128 (−399.012, −147.501)
bl_community_id70		−96.556*	−113.472**
		54.956 (−204.325, 11.213)	54.809 (−220.953, −5.991)
bl_community_id71		−267.783***	−253.371***
		51.938 (−369.634, −165.932)	52.277 (−355.886, −150.856)
bl_community_id72		−218.135***	−182.340***
		65.618 (−346.812, −89.458)	65.402 (−310.594, −54.087)
bl_community_id73		−259.240***	−234.363***
		76.617 (−409.486, −108.993)	80.102 (−391.445, −77.281)
bl_community_id74		−137.364*	−114.560
		70.371 (−275.363, 0.634)	72.785 (−257.293, 28.173)
bl_community_id75		−28.088	31.458
		69.948 (−165.257, 109.080)	67.035 (−99.999, 162.914)
bl_community_id76		−130.437**	−138.298**
		55.272 (−238.827, −22.047)	56.645 (−249.379, −27.217)
bl_community_id77		−53.063	−32.314
		62.079 (−174.801, 68.674)	62.791 (−155.448, 90.820)
bl_community_id78		−100.173*	−97.982
		60.678 (−219.163, 18.817)	61.014 (−217.632, 21.667)
bl_community_id79		−45.447	−29.613
		61.427 (−165.907, 75.013)	60.920 (−149.078, 89.852)
bl_community_id80		−84.203	−109.667*
		63.155 (−208.051, 39.645)	63.856 (−234.889, 15.555)
bl_community_id81		72.213	73.688
		63.213 (−51.749, 196.176)	63.661 (−51.152, 198.528)
bl_community_id82		−62.994	−62.198
		60.496 (−181.627, 55.639)	61.881 (−183.548, 59.151)
bl_community_id84		−99.055	−110.303
		97.295 (−289.852, 91.742)	98.058 (−302.595, 81.989)
bl_community_id85		−40.542	−53.378
		59.469 (−157.162, 76.078)	62.225 (−175.402, 68.646)
bl_community_id86		101.072	93.747
		84.618 (−64.864, 267.009)	82.156 (−67.362, 254.856)
bl_community_id87		184.121*	199.968**
		94.892 (−1.964, 370.206)	91.775 (19.997, 379.939)
bl_community_id88		129.687*	157.580**
		74.692 (−16.785, 276.160)	71.851 (16.680, 298.480)
bl_community_id89		−70.276	−52.355
		60.394 (−188.708, 48.156)	59.574 (−169.180, 64.470)
bl_community_id90		−105.744	−63.058
		109.982 (−321.420, 109.931)	102.081 (−263.240, 137.125)
bl_community_id91		−107.084	−75.897
		71.723 (−247.733, 33.564)	70.889 (−214.910, 63.117)
bl_community_id92		76.568	73.565
		95.441 (−110.593, 263.729)	94.757 (−112.254, 259.384)
bl_community_id93		166.483**	147.620**
		69.785 (29.634, 303.333)	69.785 (10.771, 284.469)
bl_community_id94		36.347	2.196
		89.975 (−140.094, 212.789)	86.474 (−167.380, 171.771)
bl_community_id95		10.341	26.809
		97.576 (−181.007, 201.688)	99.126 (−167.578, 221.195)
bl_community_id96		17.694	8.308
		82.118 (−143.340, 178.729)	83.232 (−154.911, 171.527)
bl_community_id97		−111.798	−112.707
		78.350 (−265.443, 41.847)	78.709 (−267.056, 41.642)
bl_community_id98		−45.654	−42.069
		100.402 (−242.543, 151.236)	100.891 (−239.918, 155.780)
bl_community_id99		−30.175	−53.171
		83.007 (−192.953, 132.602)	82.507 (−214.969, 108.627)
bl_community_id100		−95.443	−65.909
		74.114 (−240.780, 49.895)	76.913 (−216.736, 84.918)
bl_community_id101		52.623	78.414
		89.869 (−123.612, 228.857)	83.055 (−84.459, 241.286)
bl_community_id102		−145.194***	−154.636***
		56.261 (−255.522, −34.867)	55.358 (−263.193, −46.079)
bl_community_id103		−130.457	−153.640*
		82.796 (−292.822, 31.908)	83.014 (−316.431, 9.150)
bl_community_id104		−108.532	−77.442
		67.198 (−240.308, 23.245)	65.923 (−206.718, 51.835)
bl_community_id105		−67.163	−86.509
		91.982 (−247.541, 113.215)	90.311 (−263.609, 90.592)
bl_community_id106		13.392	13.546
		88.633 (−160.418, 187.202)	88.791 (−160.574, 187.665)
bl_community_id107		128.008	140.888*
		84.321 (−37.345, 293.362)	81.304 (−18.550, 300.326)
bl_community_id108		−139.374*	−171.672**
		77.841 (−292.022, 13.274)	80.703 (−329.931, −13.413)
bl_community_id109		32.722	47.321
		94.060 (−151.731, 217.174)	97.708 (−144.285, 238.928)
bl_community_id110		−16.395	−12.977
		76.816 (−167.031, 134.241)	77.066 (−164.104, 138.150)
bl_community_id111		−90.019	−83.294
		63.054 (−213.668, 33.630)	63.681 (−208.172, 41.584)
bl_community_id112		−27.020	−47.018
		73.687 (−171.522, 117.481)	70.487 (−185.244, 91.207)
bl_community_id113		78.801	66.194
		75.251 (−68.767, 226.370)	70.667 (−72.385, 204.773)
bl_community_id114		−122.306**	−140.940***
		56.365 (−232.838, −11.774)	54.494 (−247.803, −34.078)
bl_community_id115		−117.588	−113.213
		76.923 (−268.435, 33.259)	71.350 (−253.131, 26.704)
bl_community_id116		−19.055	−34.438
		58.203 (−133.191, 95.081)	58.860 (−149.863, 80.988)
bl_community_id117		−43.414	−35.107
		60.203 (−161.474, 74.645)	60.568 (−153.882, 83.669)
bl_hh_size		−0.962	26.689
		6.515 (−13.739, 11.814)	59.711 (−90.405, 143.784)
bl_cohort2		−17.183	−9.061
		14.960 (−46.519, 12.153)	14.573 (−37.640, 19.517)
bl_census_num_eating_groups		59.687***	48.860**
		20.799 (18.899, 100.474)	21.283 (7.124, 90.596)
bl_census_wealth_index		15.890	19.904*
		10.095 (−3.906, 35.686)	10.352 (−0.397, 40.205)
bl_loans_taken		8.840
		6.012 (−2.949, 20.629)
bl_loan_total_lent		0.067***	−0.034
		0.021 (0.026, 0.107)	0.029 (−0.091, 0.024)
bl_food_purchase_total_99		0.079	0.008
		0.075 (−0.067, 0.226)	0.095 (−0.179, 0.195)
bl_food_consumption_total_99		0.026*	0.127***
		0.014 (−0.001, 0.054)	0.048 (0.032, 0.221)
bl_days_worked_participant		3.517	−13.212
		3.350 (−3.053, 10.088)	11.564 (−35.889, 9.464)
bl_cantril_present		5.203**	5.582
		2.637 (0.031, 10.375)	8.991 (−12.050, 23.215)
bl_phq8		1.440	1.162
		2.546 (−3.552, 6.432)	6.058 (−10.718, 13.041)
bl_phq2		1.464	31.385**
		7.240 (−12.734, 15.663)	14.933 (2.102, 60.668)
bl_gad7		1.140	3.103
		2.284 (−3.339, 5.619)	5.387 (−7.461, 13.666)
bl_diener5		0.406
		1.018 (−1.589, 2.402)
bl_mental_health_average		16.338
		15.278 (−13.622, 46.299)
bl_bp_excercise		−62.834*	−56.510
		33.518 (−128.563, 2.895)	34.527 (−124.219, 11.198)
bl_med_assistance_received		31.428**	33.193**
		14.542 (2.912, 59.945)	14.377 (5.000, 61.386)
bl_shock_death_relative		12.830	12.498
		13.092 (−12.844, 38.503)	13.272 (−13.528, 38.525)
bl_shock_death_livestock		17.044	18.909
		13.784 (−9.986, 44.073)	13.669 (−7.897, 45.715)
bl_shock_religious_event		31.969*	24.866
		18.951 (−5.194, 69.131)	18.861 (−12.121, 61.853)
bl_shock_accident_injury		36.031**	32.203**
		14.367 (7.857, 64.205)	14.403 (3.959, 60.447)
bl_num_children		20.715**	24.889
		8.710 (3.635, 37.795)	22.031 (−18.313, 68.092)
bl_num_migrated		−10.639
		11.034 (−32.277, 11.000)
bl_participant_age		2.472***	8.684**
		0.686 (1.126, 3.817)	3.946 (0.945, 16.423)
bl_avg_age		1.830	3.460
		1.301 (−0.722, 4.382)	5.000 (−6.346, 13.266)
bl_expenditure_total_nonfood		−0.043**	0.001
		0.019 (−0.079, −0.006)	0.054 (−0.105, 0.107)
bl_expenditure_total_nonfood_99		0.078
		0.081 (−0.080, 0.236)
bl_gifts_food_sent		0.233*	0.248
		0.120 (−0.002, 0.468)	0.211 (−0.166, 0.661)
bl_gifts_cash_sent		−0.077**
		0.033 (−0.142, −0.013)
bl_ls_gift_given_total		0.403
		0.351 (−0.286, 1.091)
bl_ls_bought_total_99		0.290	4.663**
		0.230 (−0.161, 0.741)	2.180 (0.388, 8.938)
bl_ls_gift_given_total_99		0.500	−14.063***
		1.026 (−1.512, 2.512)	4.469 (−22.827, −5.299)
bl_dg_own_total_value_99		0.001	0.000
		0.001 (−0.001, 0.003)	0.002 (−0.003, 0.004)
bl_ag_eqp_sale_total_value		0.825**	0.579
		0.399 (0.044, 1.607)	1.032 (−1.445, 2.602)
bl_fi_index_anderson		6.967	4.747
		6.010 (−4.818, 18.752)	7.854 (−10.655, 20.149)
bl_expenditure_total_food		−0.002
		0.009 (−0.019, 0.015)
bl_expenditure_total_food_99		0.035
		0.026 (−0.017, 0.086)
bl_svg_withdrawals_99		0.140***	−0.084
		0.052 (0.038, 0.242)	0.201 (−0.478, 0.310)
bl_crop_stored_median_value		−0.000	−0.000
		0.000 (−0.001, 0.000)	0.001 (−0.001, 0.001)
bl_other_income_remittance		0.174	0.187
		0.107 (−0.036, 0.384)	0.115 (−0.039, 0.412)
bl_land_rent_value		−0.077	−0.135
		0.078 (−0.230, 0.076)	0.401 (−0.922, 0.651)
bl_asset_sales_99		0.093*	−0.088
		0.048 (−0.000, 0.186)	0.173 (−0.428, 0.252)
bl_cash_outflow_pct_gifts		−1.539	3.359
		1.720 (−4.913, 1.835)	3.386 (−3.282, 9.999)
bl_cash_outflow_pct_lent		−3.936**	−4.050
		1.832 (−7.528, −0.345)	2.852 (−9.644, 1.543)
bl_cash_netflow_99		−0.024***	−0.023***
		0.007 (−0.038, −0.010)	0.007 (−0.036, −0.009)
bl_gifts_food_sent_MISSING		−163.860**	−126.861*
		68.124 (−297.453, −30.268)	76.895 (−277.653, 23.930)
bl_expenditure_total_food_MISSING		−115.734***
		39.339 (−192.878, −38.591)
bl_land_rent_value_MISSING		−244.675***	−258.215***
		77.395 (−396.447, −92.902)	89.286 (−433.306, −83.124)
bl_food_purchase_total_phone			0.029
			0.046 (−0.061, 0.119)
bl_mental_health_index			12.440
			10.910 (−8.955, 33.835)
bl_adult_equivalent			−88.451
			145.272 (−373.331, 196.428)
bl_participant_education_years			−14.660***
			5.624 (−25.689, −3.630)
bl_gifts_cash_received			−0.285**
			0.124 (−0.528, −0.042)
bl_hh_size_SQUARED			−1.594
			3.323 (−8.111, 4.922)
bl_census_wealth_index_SQUARED			23.003
			15.109 (−6.626, 52.632)
bl_loan_total_lent_SQUARED			0.000***
			0.000 (0.000, 0.000)
bl_food_purchase_total_phone_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_food_purchase_total_99_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_food_consumption_total_99_SQUARED			−0.000**
			0.000 (−0.000, −0.000)
bl_days_worked_participant_SQUARED			1.989
			1.377 (−0.710, 4.689)
bl_cantril_present_SQUARED			−0.029
			0.943 (−1.878, 1.819)
bl_phq8_SQUARED			−0.022
			0.315 (−0.640, 0.597)
bl_phq2_SQUARED			−6.894**
			2.692 (−12.174, −1.615)
bl_gad7_SQUARED			−0.148
			0.304 (−0.745, 0.449)
bl_mental_health_index_SQUARED			14.400**
			7.190 (0.300, 28.500)
bl_pss10_z_SQUARED			−5.541
			4.740 (−14.837, 3.755)
bl_pswq16_z_SQUARED			−8.255**
			3.992 (−16.084, −0.426)
bl_diener5_z_SQUARED			−8.029
			5.408 (−18.635, 2.577)
bl_dd_child_hdds_z_SQUARED			−1.846
			3.990 (−9.671, 5.978)
bl_num_children_SQUARED			−0.371
			2.230 (−4.744, 4.003)
bl_adult_equivalent_SQUARED			10.886
			17.397 (−23.229, 45.000)
bl_participant_age_SQUARED			−0.105*
			0.054 (−0.211, 0.000)
bl_participant_education_years_SQUARED			0.927**
			0.459 (0.027, 1.828)
bl_avg_age_SQUARED			−0.001
			0.087 (−0.170, 0.169)
bl_expenditure_total_nonfood_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_gifts_food_sent_SQUARED			0.000
			0.000 (−0.001, 0.001)
bl_gifts_cash_received_SQUARED			0.000*
			0.000 (−0.000, 0.001)
bl_ls_bought_total_99_SQUARED			−0.030**
			0.015 (−0.059, −0.002)
bl_ls_gift_given_total_99_SQUARED			0.273***
			0.082 (0.112, 0.433)
bl_dg_own_total_value_99_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_ag_eqp_sale_total_value_SQUARED			0.001
			0.004 (−0.006, 0.009)
bl_fi_index_anderson_SQUARED			−1.174
			3.390 (−7.821, 5.474)
bl_svg_withdrawals_99_SQUARED			0.001
			0.000 (−0.000, 0.001)
bl_crop_stored_median_value_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_other_income_remittance_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_land_rent_value_SQUARED			0.000
			0.000 (−0.000, 0.001)
bl_asset_sales_99_SQUARED			0.000
			0.000 (−0.000, 0.001)
bl_total_consumption_99_SQUARED			0.000
			0.000 (−0.000, 0.000)
bl_cash_outflow_pct_gifts_SQUARED			−0.215**
			0.092 (−0.396, −0.034)
bl_cash_outflow_pct_lent_SQUARED			0.045
			0.036 (−0.026, 0.117)
bl_cash_netflow_99_SQUARED			−0.000
			0.000 (−0.000, 0.000)
bl_participant_education_years_MISSING			−1386.666***
			522.851 (−2411.983, −361.348)
Observations	12593	12593	12593

References

Chernozhukov, Victor, Chris Hansen, and Martin Spindler. 2016. “High-Dimensional Metrics in r,” no. arXiv:1603.01700 (August). https://doi.org/10.48550/arXiv.1603.01700.

Fitzgerald Sice, Jack, Finnian Lattimore, Tim Robinson, and Anna Zhu. 2023. “Practical Insights into Applying Double LASSO.” SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4452778.