R/proportion_non_functional_distractors.R

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

#' Proportion of Non-Functional Distractors on a Test
#'
#' Find the proportion of non-functional distractors on a test, where "non-functional" is
#' defined as a distractor which either has a positive correlation with student scores or
#' had less than 5% of students choosing it.
#'
#'@param exam A data.frame object containing a test that follows the formatting of a typical Scantron file.
#'@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).
#'@param check_format a logical value (default = TRUE) indicating whether the "exam" object should be tested
#'for correct formatting.
#'
#'@note "Non-functional" is
#' defined as a distractor which either has a positive correlation with student scores or
#' had less than 5% of students choosing it.
#'
#'@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 proportion between 0 and 1 representing the proportion od total distractors on the
#'test which were non-functional.
#'
#'@example myexam <- read.csv("scantronfile", header = TRUE, stringsAsFactors = FALSE)
#'proportion_non_functional_distractors(myexam, numchoicesperitem = rep(4, 100))
#'
#'@export
#'
#'


proportion_non_functional_distractors <- function(exam, numchoicesperitem = NULL, check_format = TRUE) {
  if (check_format == TRUE) {
    stopifnot(correct_format(exam) == TRUE)
  }
  num_items <- num_items(exam, check_format = FALSE)
  non_functional_both_criteria <- non_functional_both_criteria(exam, numchoicesperitem, check_format = FALSE)
  total_number_of_distractors <- total_number_of_distractors(exam, numchoicesperitem, check_format = FALSE)
  return(length(unlist(non_functional_both_criteria)) / total_number_of_distractors)
}