irt (version 0.2.9)

distractor_analysis: Distractor Analysis Function

Description

Distractor Analysis Function

Usage

distractor_analysis(resp, key = NULL, ip = NULL, criterion = NULL)

Value

A data.frame with following columns

'item_id'

Item identifier

'key'

Answer key

'option'

The selected option

'n'

Number of subjects/examinees answered this item

'prop'

Observed proportions of the choice.

'bis'

Biserial correlation between the examinees selected the choice and the total scores.

'pbis'

Point-biserial correlation between the examinees selected the choice and the total scores.

'bis_adj'

Biserial correlation between item and total score without this item. Sum scores will be used in the calculation of 'bis_adj' even 'criterion' is provided.

'pbis_adj'

Point-biserial correlation between item and total score without this item. Sum scores will be used in the calculation of 'bis_adj' even 'criterion' is provided.

Arguments

resp

It can be either a Response_set-class object with valid raw responses; or, a matrix or data.frame containing the raw item responses.

key

The answer key for the responses. Keys can also be provided via ip argument.

ip

An Itempool-class object that contains the keys of the items. The program will look check whether a ip$misc$key is specified for all items. Valid keys should be provided via ip if key argument is NULL.

criterion

Provide a continuous criterion variable such as a total raw score, or theta score that will be used in the calculation of correlation calculations. If this value is NULL, the total score will be used.

Author

Emre Gonulates

Examples

n_item <- 10 # sample(8:12, 1)
n_theta <- 50 # sample(100:200, 1)
raw_resp <- matrix(sample(LETTERS[1:4], n_item * n_theta, replace = TRUE),
                   nrow = n_theta, ncol = n_item,
                   dimnames = list(paste0("Examinee-", 1:n_theta),
                                   paste0("Item-", 1:n_item)))
# Add some missing responses
raw_resp[sample(1:length(raw_resp), round(length(raw_resp)*.1))] <- NA
# Prepare answer key
key <- sample(LETTERS[1:4], n_item, replace = TRUE)

# Run distractor analysis:
da <- distractor_analysis(resp = raw_resp, key = key)