covarTest_dis: Testing for balanced covariates: equality of distribution In bquast/RDDtools: Toolbox for Regression Discontinuity Design ('RDD')

Description

Tests equality of distribution with a Kolmogorov-Smirnov for each covariates, between the two full groups or around the discontinuity threshold

Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```covarTest_dis( object, bw, exact = NULL, p.adjust = c("none", "holm", "BH", "BY", "hochberg", "hommel", "bonferroni") ) ## S3 method for class 'rdd_data' covarTest_dis( object, bw = NULL, exact = FALSE, p.adjust = c("none", "holm", "BH", "BY", "hochberg", "hommel", "bonferroni") ) ## S3 method for class 'rdd_reg' covarTest_dis( object, bw = NULL, exact = FALSE, p.adjust = c("none", "holm", "BH", "BY", "hochberg", "hommel", "bonferroni") ) ```

Arguments

 `object` object of class rdd_data `bw` a bandwidth `exact` Argument of the `ks.test` function: NULL or a logical indicating whether an exact p-value should be computed. `p.adjust` Whether to adjust the p-values for multiple testing. Uses the `p.adjust` function

Value

A data frame with, for each covariate, the K-S statistic and its p-value.

Author(s)

Matthieu Stigler <Matthieu.Stigler@gmail.com>

`covarTest_mean` for the t-test of equality of means
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18``` ```data(house) ## Add randomly generated covariates set.seed(123) n_Lee <- nrow(house) Z <- data.frame(z1 = rnorm(n_Lee, sd=2), z2 = rnorm(n_Lee, mean = ifelse(house<0, 5, 8)), z3 = sample(letters, size = n_Lee, replace = TRUE)) house_rdd_Z <- rdd_data(y = house\$y, x = house\$x, covar = Z, cutpoint = 0) ## Kolmogorov-Smirnov test of equality in distribution: covarTest_dis(house_rdd_Z, bw=0.3) ## Can also use function covarTest_dis() for a t-test for equality of means around cutoff: covarTest_mean(house_rdd_Z, bw=0.3) ## covarTest_dis works also on regression outputs (bw will be taken from the model) reg_nonpara <- rdd_reg_np(rdd_object=house_rdd_Z) covarTest_dis(reg_nonpara) ```