| RSM {eRm} | R Documentation |
This function computes the parameter estimates of a rating scale model for polytomous item responses by using CML estimation.
RSM(X, W)
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. |
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.
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. |
Missing Values are not allowed in X. All items must have the same number of response categories.
Patrick Mair, Reinhold Hatzinger
Fischer, G. H., and Molenaar, I. (1995). Rasch Models - Foundations, Recent Developements, and Applications. Springer.
print.eRm,coef.eRm,vcov.eRm,model.matrix.eRm,plot.Rm,
summary.Rm
#PCM with 10 subjects, 3 items data(X_rsm) res <- RSM(X_rsm) res