RSM {eRm}R Documentation

Estimation of rating scale models

Description

This function computes the parameter estimates of a rating scale model for polytomous item responses by using CML estimation.

Usage

RSM(X, W)

Arguments

X Input data matrix or data frame with item responses (starting from 0); rows represent individuals, columns represent items.
W Design matrix for the RSM. If omitted, the function will compute W automatically.

Details

The design matrix approach transforms the RSM into a partial credit model and estimates the corresponding basic parameters by using CML. Available methods for RSM-objects are print, coef, model.matrix, vcov, plot, summary.

Value

Returns an object of class Rm and contains the log-likelihood value, the parameter estimates and their standard errors.

loglik The log-likelihood.
iter Number of iterations required.
etapar Estimated basic item parameters.
se_eta Standard errors of the estimated basic item parameters.
betapar Estimated item parameters.
LR The log-likelihood test statistic for the model.

Note

Missing Values are not allowed in X. All items must have the same number of response categories.

Author(s)

Patrick Mair, Reinhold Hatzinger

References

Fischer, G. H., and Molenaar, I. (1995). Rasch Models - Foundations, Recent Developements, and Applications. Springer.

See Also

print.eRm,coef.eRm,vcov.eRm,model.matrix.eRm,plot.Rm, summary.Rm

Examples


#PCM with 10 subjects, 3 items

data(X_rsm)
res <- RSM(X_rsm)
res              

[Package eRm version 0.3 Index]