calctheta {lordif} | R Documentation |
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 <choi.phd@gmail.com>
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
Examples
## Not run: calctheta(ipar,resp.data,model="GPCM")