R/pwr.base_n.r

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

pwr_base_n.version = "0.3.5";

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

#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--------------------------------------------------

#' pwr.base_n
#'
#' This function finds base-n based on smallest number of participants (>10) needed to reach power >= .95
#' @param x Group 1
#' @param y Group 2
#' @param alpha alpha value for testing, defaults to .05
#' @param power pwr criteria, defaults to .95
#' @param paired.sample Boolean to run Paired-Sample t-Test, defaults to FALSE
#' @keywords base-n, pwr
#' @export
#' @examples
#' pwr_base_n(group1, group2, .85, paired.sample=TRUE)
#' pwr_base_n(group1, group2, power=.95)

#####Function Start

pwr.base_n <- function(g1, g2, alpha=.05, power=.85, paired=FALSE) {

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


#Assign group data
group1 <- g1;
group2 <- g2;


# 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) {

			#Makes sure variance is non-zero prior to running ind-sample t-test
			if (var(group1[1:k]) != 0 & var(group2[1:k]) != 0){

				#Saves iterative p values
				p_value <- t.test(group1[1:k],group2[1:k])$p.value;

				#save effect size
				d_value <- cohen.d(group1[1:k],group2[1:k])$estimate;

				#Saves iterative power values
				pwr_value <- pwr.t.test(n=k, d_value, sig.level=alpha, power=NULL, type="two.sample")$power;

				#combine current iteration results to new row
				pwr.results <- rbind(pwr.results, list(k, p_value, d_value, pwr_value), stringsAsFactors=FALSE);

			#If variance = 0, return n as -1 value
			} else {
				return(list(participants = -1))
			}
		} #end if


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

			#Makes sure there is variance before running paired sample t-test
			if (sd(group1[1:k] - group2[1:k]) != 0 ){

				# tryCatch
				tryCatch({ #checks for errors

					#Saves iterative p values in pwr.results
					p_value <- t.test(group1[1:k],group2[1:k], paired = TRUE)$p.value;

					#save effect size
					d_value <- cohen.d(group1[1:k], group2[1:k])$estimate;

					#save iterative power test in pwr.results
					pwr_value <- pwr.t.test(n = k, d_value, sig.level = alpha, power = NULL, type = "paired")$power;

					#combine current iteration results with data frame
					pwr.results <- rbind(pwr.results, list(k, p_value, d_value, pwr_value), stringsAsFactors=FALSE);

				},

				#If there is an error, return n as -1
				error = function(err) {
				  return(list(participants = -1))
				}); #End tryCatch---

			#If there is not variance, return n as -1
			 } else {
			  return(list(participants = -1))
			}
		} #end if

} #end for loop


### Return base_n ------------

	min_n <- 10;

	#get first row that is >= power and >= min_n
	min_power = head(pwr.results[pwr.results$power >= power & pwr.results$participants >= min_n,], 1);

###### If power criteria IS met---------------

	if (!is.null(min_power$participants) & length(min_power$participants) > 0) {

	  # return participants, p.value, d, and power of row
	  return(list(participants = min_power[1,1], p.value = min_power[1,2], d = min_power[1,3], power = min_power[1,4]));


##### if power criteria NOT met
} else {

    #if no power levels matching criterion are found, return base_n as 0 with summary data.
    #max_pwr = max( pwr.results$power[10:NROW(pwr.results$power)]);
    #sample_pwr = pwr.results$power[NROW(pwr.results$power)];

    n = 0;

    return(participants = n);

  }
}