#' validate
#'
#' Provides some diagnostics on the goodness of control fit to the test groups:
#' average difference, proportion of difference to test group average, and if
#' there are any duplicats present in the controls.
#'
#' If there are duplicates in the controls, the functions output will be a vector
#' of row numbers which contain the duplicated controls.
#'
#' @param output_df The data frame that contains all tests and selected controls
#' @export
#' @author Nicholas Sun <nicholas.sun@rutgers.edu>
#' @examples
#' output <- one_factor_search(raw_tests, raw_controls)
#' validate(output)
validate <- function (output_df) {
diff <- (mean(output_df$Test_Sales) - mean(output_df$Control_Sales))
print(paste("The average difference between test and controls is", toString(diff)))
diff.prop <- (mean(output_df$Control_Sales) - mean(output_df$Test_Sales))/mean(output_df$Test_Sales)
print(paste("This difference is", toString(diff.prop),"% of the test group average"))
dupes <- duplicated(output_df$Control_ID)
if ((length(dupes[dupes == "TRUE"])) == 0){
print("There are no duplicates in the selected controls.")
}else{
print("There are duplicates in the selected controls, located in the following rows:")
dupes.locs <- which(dupes)
print(dupes.locs)
}
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.