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)

### 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 |

### Details

Basically combines `score.items`

with a conversion from multiple choice to right/wrong.

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

### 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

### See Also

`score.items`

, `omega`

### Examples

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

[Package

*psych* version 1.0-68

Index]