pcIRT-package: IRT Models for Polytomous and Continuous Item Responses

Description Details Author(s) References See Also Examples

Description

The multidimensional polytomous Rasch model (Rasch, 1961) can be estimated with pcIRT. It provides functions to set linear restrictions on the item category parameters of this models. With this functions it is possible to test whether item categories can be collapsed or set as linear dependent. Thus it is also possible to test whether the multidimensional model can be reduced to a unidimensional model that is whether item categories represent a unidimensional continuum. For this case the scoring parameter of the categories is estimated.

Details

This package estimates the Continuous Rating Scale model by Mueller (1987). It is an extension of the Rating Scale Model by Andrich (1978) on continuous responses (e.g. taken by a visual analog scale).

Package: pcIRT
Type: Package
Version: 0.1
Date: 2013-11-13
License: GPL-3

Author(s)

Christine Hohensinn Maintainer: Christine Hohensinn <[email protected]>

References

Andersen, E. B. (1995). Polytomous Rasch models and their estimation. In G. H. Fischer and I. Molenaar (Eds.). Rasch Models - Foundations, Recent Developements, and Applications. Springer.

Fischer, G. H. (1974). Einfuehrung in die Theorie psychologischer Tests [Introduction to test theory]. Bern: Huber.

Hohensinn, C. (2018). pcIRT: An R Package for Polytomous and Continuous Rasch Models. Journal of Statistical Software, Code Snippets, 84(2), 1-14. doi:10.18637/jss.v084.c02

Mueller, H. (1987). A Rasch model for continuous ratings. Psychometrika, 52, 165-181.

Rasch, G. (1961). On general laws and the meaning of measurement in psychology, Proceedings Fourth Berekely Symposium on Mathematical Statistiscs and Probability 5, 321-333.

See Also

MPRM CRSM

Examples

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#simulate data set according to the multidimensional polytomous Rasch model (MPRM)
simdat <- simMPRM(rbind(matrix(c(-1.5,0.5,0.5,1,0.8,-0.3, 0.2,-1.2), ncol=4),0), 500)

#estimate MPRM item parameters
res_mprm <- MPRM(simdat$datmat)

summary(res_mprm)

pcIRT documentation built on May 1, 2019, 11:09 p.m.