RM {eRm}R Documentation

Estimation of Rasch Models

Description

This function computes the parameter estimates of a Rasch model for binary item responses by using CML estimation.

Usage

RM(X, W)

Arguments

X Input 0/1 data matrix or data frame; rows represent individuals, columns represent items.
W Design matrix for the Rasch model. If omitted, the function will compute W automatically.

Details

For estimating the item parameters the CML method is used. Available methods for RM-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.

model Type of model.
loglik The log-likelihood.
df Degrees of freedom.
iter Number of iterations required.
etapar Estimated basic item parameters.
se_eta Standard errors of the estimated basic item parameters.
hessian Hessian matrix.
betapar Estimated item parameters.
LR The log-likelihood test statistic for the model.
W Design matrix.
etaparG1 Parameters for first LR-group.
etaparG2 Parameters for second LR-group.

Note

Missing Values are not allowed in X, the category coding must start with 0 (lowest category).

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.eRm

Examples


#Rasch model with 30 items, 100 persons

data(raschdat)
res <- RM(raschdat)
res
summary(res)                
plot(res)                   

[Package eRm version 0.3.2 Index]