ims {msd}

Item Measures

Description

Estimates item measures assuming person measures are known and all persons use the same set of rating category thresholds.

Usage

ims(data, persons, thresholds, misfit = FALSE, minRating = NULL)

Arguments

data

a numeric matrix of ordinal rating scale data whose entries are integers with missing data set to NA. Rows are persons and columns are items. The ordinal rating scale is assumed to go from the smallest to largest integer in integer steps unless minRating is specified (see Details).

persons

a numeric vector of person measures with missing values set to NA. The length of persons must equal the number of rows in data.

thresholds

a numeric vector of ordered rating category thresholds with no NA.

misfit

logical for calculating infit and outfit statistics. Default is FALSE.

minRating

integer representing the smallest ordinal rating category. Default is NULL (see Details).

Details

minRating must be specified if either the smallest or largest possible rating category is not in data (i.e., no person used one of the extreme rating categories). If minRating is specified, the ordinal rating scale is assumed to go from minRating to minRating + length(thresholds) in integer steps.

Value

A list whose elements are:

item_measures

a vector of person measures for each person

item_std_errors

a vector of standard errors for the persons

infit_items

if misfit = TRUE, a vector of infit statistics for the items

outfit_items

if misfit = TRUE, a vector of outfit statistics for the items

Note

Item measures estimated with ims differ from those estimated with msd because ims assumes all persons use the same rating category thresholds while msd does not. Intended use of ims is with an anchored set of persons and thresholds. Item measures that cannot be estimated will return as NA (e.g., if all responses to an item consist of only the highest rating category, or of only the lowest rating category, that item's item measure cannot be estimated).

Author(s)

Chris Bradley ([e-mail])

See Also

msd

Examples

# Simple example with randomly generated values and lowest rating category = 0.
d <- as.numeric(sample(0:4, 500, replace = TRUE))
dm <- matrix(d, nrow = 50, ncol = 10)
pm <- runif(50, -2, 2)
th <- sort(runif(4, -2, 2))
im <- ims(data = dm, persons = pm, thresholds = th, misfit = TRUE, minRating = 0)