psych (version 1.0-95)

score.multiple.choice: Score multiple choice items and provide basic test statistics

Description

Ability tests are typically multiple choice with one right answer. score.multiple.choice takes a scoring key and a data matrix (or data.frame) and finds total or average number right for each participant. Basic test statistics (alpha, average r, item means, item-whole correlations) are also reported.

Usage

score.multiple.choice(key, data, score = TRUE, totals = FALSE, ilabels = NULL, missing = TRUE, impute = "median", digits = 2,short=TRUE)

Arguments

key
A vector of the correct item alternatives
data
a matrix or data frame of items to be scored.
score
score=FALSE, just convert to right (1) or wrong (0). score=TRUE, find the totals or average scores and do item analysis
totals
total=FALSE: find the average number correct total=TRUE: find the total number correct
ilabels
item labels
missing
missing=TRUE: missing values are replaced with means or medians mising=FALSE missing values are not scored
impute
impute="median", replace missing items with the median score impute="mean": replace missing values with the item mean
digits
How many digits of output
short
short=TRUE, just report the item statistics, short=FALSE, report item statistics and subject scores as well

Value

  • scoresSubject scores on one scale
  • missingNumber of missing items for each subject
  • item.statsscoring key, response frequencies, item whole correlations, n subjects scored, mean, sd, skew, kurtosis and se for each item
  • alphaCronbach's coefficient alpha
  • av.rAverage interitem correlation

Details

Basically combines score.items with a conversion from multiple choice to right/wrong.

The item-whole correlation is inflated because of item overlap.

See Also

score.items, omega

Examples

Run this code
data(iqitems)
iq.keys <- c(4,4,3,1,4,3,2,3,1,4,1,3,4,3)
score.multiple.choice(iq.keys,iqitems)
#just convert the items to true or false 
iq.tf <- score.multiple.choice(iq.keys,iqitems,score=FALSE)
describe(iq.tf)  #compare to previous results

Run the code above in your browser using DataCamp Workspace