R/iterative.ttest.r

In baileymh/Shuffle: What the Package Does (One Line, Title Case)

iterative.ttest.version = "0.1";

# Required packages-----------
packages = c("pwr", "effsize", "ggplot2");

#use this function to check if each package is on the local machine
#if a package is installed, it will be loaded
#if any are not, the missing package(s) will be installed and loaded
package.check <- lapply(packages, FUN = function(x) {
  if (!require(x, character.only = TRUE)) {
    install.packages(x, dependencies = TRUE)
    library(x, character.only = TRUE);
  }
})
###### End Packages

###### Documentation--------------------------------------------------

#' iterative.ttest()
#'
#' This function incrementally increases the number of participants and does t.test for each
#' @param x Group 1
#' @param y Group 2
#' @param alpha alpha value for testing, defaults to .05
#' @param paired Boolean to run Paired-Sample t-Test, defaults to FALSE
#' @keywords iterative, t.test, p trend
#' @export
#' @examples
#' iterative.ttest(group1, group2, alpha=.01 paired=TRUE)


iterative.ttest <- function(x, y, alpha=.05, paired = FALSE) {


  # initialize results variable as data frame to keep participants, p values, effect size, and power values
  results <- data.frame("participants"= 1, "statistic" = 1, "df" = 0, "p.value" = 1);


  #Assign group data
  group1 <- x;
  group2 <- y;


  # Incremental t-Tests========================
  #i.e. 1-2, 1-3, 1-4, 1-5, etc..

  for(k in 2:length(group1)) {

    ### Paired Sample = FALSE -------------------------
    # Run independant Sample
    if (paired == FALSE || missing(paired) == TRUE) {

        test_results <- t.test(group1[1:k],group2[1:k]);

        #combine current iteration results to new row
        results <- rbind(results, list(k, test_results$statistic, test_results$parameter, test_results$p.value), stringsAsFactors=FALSE);

    } #end if


    # Paired Sample = TRUE ----------------
    # Run paired Sample
    if (paired == TRUE) {

      test_results <- t.test(group1[1:k],group2[1:k], paired=TRUE);

      #combine current iteration results to new row
      results <- rbind(results, list(k, test_results$statistic, test_results$parameter, test_results$p.value), stringsAsFactors=FALSE);

    } #end if

  } #end for loop

  assign("iterative_test",results, envir=.GlobalEnv);

  ggplot(iterative_test, aes(iterative_test$participants, iterative_test$p.value)) +
    geom_point() +
    xlab("Participants") +
    ylab("p value") +
    geom_hline(yintercept=alpha, linetype="dashed", color = "red")

}