# item_analysis: Item Analysis Function In irt: Item Response Theory and Computerized Adaptive Testing Functions

## Description

Item Analysis Function

## Usage

 `1` ```item_analysis(resp, criterion = NULL, ip = NULL, suppress_output = FALSE) ```

## Arguments

 `resp` A `Response_set-class` object, `matrix` or `data.frame` containing the item responses. `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. `ip` An `Itempool-class` object. This will help function in two ways. First, if the `resp` is a `Response_set-class` object, the function will help the responses to be arranged in the same order as `ip`. Second, if there are polytomous items in the data, `ip` will help finding the maximum values of each item. Otherwise, the maximum values each item can take will be calculated using data, which may be fallible. `suppress_output` If `TRUE`, the function will suppress console output. Default value is `FALSE`

## Value

A list of

'item_id'

Item ID.

'n'

Number of examinees responded this item.

'pval'

p-value, proportion of examinees correctly answered items. If there are polytomous items in the data, p-value will be calculated by dividing the mean of the scores for the item by the maximum possible score of the item.

'pbis'

Point biserial correlation.

'bis'

Biserial correlation.

Point biserial correlation between item and total score without this item.

Biserial correlation between item and total score without this item.

Emre Gonulates

## Examples

 ```1 2 3 4 5 6 7``` ```theta <- rnorm(100) ip <- generate_ip(n = 20) resp <- sim_resp(ip = ip, theta = theta, prop_missing = .2) # Item analysis based on total scores item_analysis(resp) # Item analysis based on theta scores item_analysis(resp, criterion = theta) ```

irt documentation built on Nov. 9, 2021, 9:07 a.m.