calctheta: calculates EAP theta estimates and associated standard errors

In lordif: Logistic Ordinal Regression Differential Item Functioning using IRT

calculates EAP theta estimates and associated standard errors

Description

Calculates Expected A Posteriori (EAP) theta estimates and associated standard error estimates (posterior standard deviations).

Usage

  calctheta(ipar, resp.data, theta, prior.mean = 0, prior.sd = 1, model = "GRM")

Arguments

ipar	a data frame containing the following columns: a, cb1, cb2,..., cb(maxCat)
resp.data	a data frame containing item responses
theta	a theta grid (quadrature points)
prior.mean	prior mean
prior.sd	prior standard deviation
model	IRT model, either "GRM" or "GPCM")

Details

Calculates EAP theta estimates and standard error estimates based on the input item parameters (ipar), the item response data (resp.data), and the IRT model specified ("GRM" or "GPCM").

Value

A list object with the following components

EAP	Expected A Posteriori estimates of theta
SE	Standard Error estimates

Note

Some missing item responses (NA) are allowed.

Author(s)

Seung W. Choi <[e-mail]>

References

Bock, R. D. & Mislevy, R. J. (1982). Adaptive EAP Estimation of Ability in a Microcomputer Environment. Applied Psychological Measurement, 6(4), 431-444.

See Also

calcprob, probgrm, probgpcm

Examples

  ## Not run: calctheta(ipar,resp.data,model="GPCM")

lordif documentation built on April 3, 2025, 10:37 p.m.