Nothing
#' @title Random Assignment Generator for a Factorial Experiment with Many Conditions
#'
#' @description This function provides a list of random numbers that can be used to assign
#' participants to conditions (cells) in an experiment with many conditions, such as a factorial
#' experiment. The randomization is restricted as follows: if the number of participants
#' available is a multiple of the number of conditions, then cell sizes will be
#' balanced; otherwise, they will be as near balanced as possible.
#'
#'
#' @param N The total number of participants to be randomized.
#' @param C The total number of conditions for the experiment you are planning. Note that f
#' or a complete factorial experiment having k factors, there will be 2^k conditions.
#'
#' @return A dataframe with 1 variable ranList with N observations, each observation of ranList
#' provides a random number for each participant. This will be a number from 1 to C.
#' For example, if the 4th number in the list is 7, the 4th subject is randomly assigned
#' to experiment condition 7. Random numbers will be generated so that the experiment is
#' approximately balanced.
#'
#' @export RandomAssignmentGenerator
#' @examples
#' result <- RandomAssignmentGenerator(35,17)
#' print(result)
RandomAssignmentGenerator <- function(N,
C){
numloop <- N %/% C;
size1 <- N %% C;
ranList <- c();
for(i in 1:numloop) {
tmp <- sample(1:C,size=C,replace=FALSE);
ranList <- append(ranList,tmp);
}
tmp <- sample(1:C,size=size1,replace=FALSE);
ranList <- append(ranList,tmp);
#print(ranList);
result <- data.frame(ranList);
return(result);
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.