score.multiple.choice function

Score multiple choice items and provide basic test statistics

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.

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

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

  missing=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

• skew: Should the skews and kurtosi of the raw data be reported? Defaults to FALSE because what is the meaning of skew for a multiple choice item?

Details

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

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

The example data set is taken from the Synthetic Aperture Personality Assessment personality and ability test at https://www.sapa-project.org/.

Returns

• scores: Subject scores on one scale

• missing: Number of missing items for each subject

• item.stats: scoring key, response frequencies, item whole correlations, n subjects scored, mean, sd, skew, kurtosis and se for each item

• alpha: Cronbach's coefficient alpha

• av.r: Average interitem correlation

Author(s)

William Revelle

See Also

score.items, omega

Examples

if(require(psychTools)) {
data(psychTools::iqitems)
iq.keys <- c(4,4,4, 6,6,3,4,4,  5,2,2,4,  3,2,6,7)
score.multiple.choice(iq.keys,psychTools::iqitems)
#just convert the items to true or false 
iq.tf <- score.multiple.choice(iq.keys,psychTools::iqitems,score=FALSE)
describe(iq.tf)  #compare to previous results
}