eRm (version 0.9.0)

Waldtest: 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 c

x

Object of class wald.

...

Further arguments passed to or from other methods. They are ignored in this function.

Value

• Returns an object of class wald containing:
• etapar1
  Eta parameters for first subgroup
• se1
  Standard errors for first subgroup
• etapar2
  Eta parameters for second subgroup
• se2
  Standard errors for second subgroup

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.

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 f�r das probabilistische Testmodell von Rasch [Algorithms and programs for Rasch's probabilistic test model]. Psychologische Beitr�ge, 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)