score.multiple.choice {psych} R Documentation

## 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,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 http://test.personality-project.org.

### Value

 `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

`score.items`, `omega`

### Examples

```data(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,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

```

[Package psych version 1.7.8 ]