This function computes the parameter estimates of a partial credit model for polytomous item responses by using CML estimation.
UTF-8
PCM(X, W, se =TRUE, sum0 =TRUE, etaStart)
Arguments
X: Input data matrix or data frame with item responses (starting from 0); rows represent individuals, columns represent items. Missing values are inserted as NA.
W: Design matrix for the PCM. If omitted, the function will compute W automatically.
se: If TRUE, the standard errors are computed.
sum0: If TRUE, the parameters are normed to sum-0 by specifying an appropriate W. If FALSE, the first parameter is restricted to 0.
etaStart: A vector of starting values for the eta parameters can be specified. If missing, the 0-vector is used.
Details
Through specification in W, the parameters of the categories with 0 responses are set to 0 as well as the first category of the first item. Available methods for PCM-objects are:
Fischer, G. H., and Molenaar, I. (1995). Rasch Models - Foundations, Recent Developements, and Applications. Springer.
Mair, P., and Hatzinger, R. (2007). Extended Rasch modeling: The eRm package for the application of IRT models in R. Journal of Statistical Software, 20(9), 1-20.
Mair, P., and Hatzinger, R. (2007). CML based estimation of extended Rasch models with the eRm package in R. Psychology Science, 49, 26-43.
Author(s)
Patrick Mair, Reinhold Hatzinger
See Also
RM,RSM,LRtest
Examples
##PCM with 10 subjects, 3 itemsres <- PCM(pcmdat)res
summary(res)#eta and beta parameters with CIthresholds(res)#threshold parameters