RM {eRm} | R Documentation |
This function computes the parameter estimates of a Rasch model for binary item responses by using CML estimation.
RM(X, W)
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. |
For estimating the item parameters the CML method is used.
Available methods for RM-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.
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. |
Missing Values are not allowed in X, the category coding must start with 0 (lowest category).
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.eRm
#Rasch model with 30 items, 100 persons data(raschdat) res <- RM(raschdat) res summary(res) plot(res)