Waldtest {eRm}R Documentation

Item-Specific Wald Test

Description

Performs a Wald test on item-level by splitting subjects into subgroups.

Usage

## S3 method for class 'Rm':
Waldtest(object, splitcr = "median")
## S3 method for class 'wald':
print(x,...)

Arguments

object Object of class RM.
splitcr Split criterion for subject raw score splitting. median uses the median as split criterion, mean performs a mean-split. Optionally splitcr can also be a dichotomous vector which assigns each person to a certain subgroup (e.g., following an external criterion).
x Object of class wald.
... Further arguments passed to or from other methods. They are ignored in this function.

Details

The Wald test only works if both subgroups have the same parameters. For instance, for small samples in RSM or PCM the user must find an appropriate split such that in each subgroup the same item-category parameters occur.

Value

Returns an object of class wald containing:

coef.table Data frame with test statistics, z- and p-values.
etapar1 Eta parameters for first subgroup
se1 Standard errors for first subgroup
etapar2 Eta parameters for second subgroup
se2 Standard errors for second subgroup

Note

Author(s)

Patrick Mair, Reinhold Hatzinger

References

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

Fischer, G. H., and Scheiblechner, H. (1970). Algorithmen und Programme für das probabilistische Testmodell von Rasch [Algorithms and programs for Rasch's probabilistic test model]. Psychologische Beiträge, 12, 23-51.

See Also

Waldtest

Examples


#Wald test for dichotomous Rasch model with median subject split
data(raschdat1)
res <- RM(raschdat1)
Waldtest(res)

#Wald test with user-defined subject split
splitvec <- sample(1:2,100,replace=TRUE)
Waldtest(res, splitcr = splitvec)


[Package eRm version 0.9.1.1 Index]