eRm (version 0.9-2)

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:
• coef.table
  Data frame with test statistics, z- and p-values.
• betapar1
  Beta parameters for first subgroup
• se.beta1
  Standard errors for first subgroup
• betapar2
  Beta parameters for second subgroup
• se.beta2
  Standard errors for second subgroup

Details

Items are eliminated if they not have the same number of categories in each subgroup. To avoid this problem, for RSM and PCM it is considered to use a random or another user-defined split.

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 fuer das probabilistische Testmodell von Rasch [Algorithms and programs for Rasch's probabilistic test model]. Psychologische Beitraege, 12, 23-51.

See Also

LRtest

Examples

#Wald test for Rasch model with user-defined subject split
data(raschdat2)
res <- RM(raschdat2)
splitvec <- sample(1:2,25,replace=TRUE)
Waldtest(res, splitcr = splitvec)

#Wald test for RSM eliminates 4 items (with median split)
data(rsmdat)
res <- RSM(rsmdat)
Waldtest(res)