R/num_choices_per_item.R

In melissavanbussel/Analyze-Scantron: Analyze your multiple choice test

#' Number of choices for each question on a test
#'
#' Finds the number of choices that were available for each question on a test.
#'
#'@param exam A data.frame object containing a test that follows the formatting of a typical Scantron file.
#
#'@param check_format a logical value (default = TRUE) indicating whether the "exam" object should be tested
#'for correct formatting.
#'
#'@param numchoicesperitem A vector which has the same length as the number of questions on the test, where each element in
#'the vector corresponds to the number of choices there were for each of the questions on the test. For example, if your
#'test had 35 questions which each had 5 options, numchoicesperitem = rep(5, 35). Defaults to NULL; if left NULL,
#'the function will estimate the number of choices for each question by finding the "largest" option selected by students.
#'For example, if a student chose "E", but no students chose "F", then the function would guess that there were 5 choices
#'for that question.
#'
#'@note The argument "exam" must be in the format of a typical Scantron results file.
#'Column 1 should correspond to ID (e.g., student number); column  2 should correspond to
#'DEPT (e.g., MATH); column 3 should correspond to COURSE CODE (e.g., 1051); the remaining
#'columns should each correspond to one of the questions on the test. The header of the data
#'frame should contain the column names, and row 1 of the data frame should contain the answer
#'key for the test. For example, if you had an exam with 25 students and 40 questions,
#'the data.frame object should have 26 rows and 43 columns.
#'
#'@note The "check_format" argument defaults to null. If this is left as null, the function will call
#'the \code{\link{num_choices_per_item}} function, which will do its best to guess the number of options
#'for each question. This is done by looking at the student answers and finding the
#'"largest" answer for each question. For example, if at least one student answered "E", but no students
#'answered "F", the function would guess that there were 5 options for that question.
#'
#'@return Returns a numeric vector which is the same length as the number of questions on the test.
#'Each element in the vector corresponds to one of the questions on the test, where the element
#'contains the number of choices for that question.
#'
#'
#'@export
#'


num_choices_per_item <- function(exam, numchoicesperitem = NULL, check_format = TRUE){
  if(check_format == TRUE){
    stopifnot(correct_format(exam) == TRUE)
  }
  # Check if the user's numchoicesperitem makes sense, if they chose to include it
  if (!is.null(numchoicesperitem) == TRUE) {
    stopifnot(is.vector(numchoicesperitem), is.numeric(numchoicesperitem), length(numchoicesperitem) == num_items(exam, check_format = FALSE))
  }
  if (!is.null(numchoicesperitem)) {
    num_choices_per_item <- numchoicesperitem
  } else {
    num_items <- num_items(exam, check_format = TRUE)
    num_students <- num_students(exam, check_format = TRUE)
    student_data <- student_data(exam, check_format = TRUE)
    num_choices_per_item <- vector(length = num_items)
    for (j in 1:num_items) {
      temp <- vector(length = num_students)
      for (i in 1:num_students) {
        if (student_data[i,j] != "BLANK" & grepl(",", student_data[i,j]) == FALSE ) {
          temp[i] <- letter2num(unlist(student_data[i, j]))
        }
      }
      num_choices_per_item[j] <- max(temp)
    }
  }
  return(num_choices_per_item)
}