calctheta {lordif}

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")