impact_eval: Impact Evaluation of Treatment Effects

In RCT: Assign Treatments, Power Calculations, Balances, Impact Evaluation of Experiments

Impact Evaluation of Treatment Effects

Description

Impact Evaluation of Treatment Effects

Usage

impact_eval(
  data,
  endogenous_vars,
  treatment,
  heterogenous_vars,
  cluster_vars = "0",
  fixed_effect_vars = "0",
  control_vars
)

Arguments

data	A data.frame, tibble or data.table
endogenous_vars	Vector of Y's on which treatment effects will be evaluated
treatment	Variable indicating the treatment status
heterogenous_vars	Vector of variables for which you wish to assess treatment distributions/heterogeneities.
cluster_vars	Vector of variables to cluster the standard errors. Default is without clustered std errors
fixed_effect_vars	Vector of variables to add as fixed effects. Default is without fixed effects
control_vars	Vector of variables to control for in the evaluation. Default is without controls

Details

This function carries out the evaluation of treatment effects on endogenous variables. It automatically runs the regressions of all the endogenous_vars supplied & all the combinations of endogenous_vars and heterogenous_vars. Additionally, the function has the option of include fixed_effects, controls and cluster variables for clustered std errors.

Value

impact_eval() returns a list of regression tables. The names of the list are the same as the endogenous variables. for heterogeneities the names are endogenous_var_heterogenous_var

Examples

data <- data.frame(y_1 = rnorm(n = 100, mean = 100, sd = 15), 
                  y_2 = rnorm(n = 100, mean = 8, sd = 2), 
                  treat = rep(c(0,1,2,3), each = 25), 
                  heterogenous_var1 = rep(c("X_Q1", "X_Q2", "X_Q3", "X_Q4"), times = 25),
                  cluster_var1 = rep(c(1:5), times = 20), 
                  fixed_effect_var1 = rep(c(1,2), times = 50),
                  control_var1 = rnorm(n = 100, mean = 20, sd = 1))

evaluation<-impact_eval(data = data, 
                       endogenous_vars = c("y_1", "y_2"), 
                       treatment = "treat", 
                       heterogenous_vars = c("heterogenous_var1"), 
                       cluster_vars = "cluster_var1", fixed_effect_vars = c("fixed_effect_var1"), 
                       control_vars = c("control_var1"))

RCT documentation built on May 13, 2022, 9:06 a.m.