Waldtest {eRm} | R Documentation |
Performs a Wald test on item-level by splitting subjects into subgroups.
## S3 method for class 'Rm'
Waldtest(object, splitcr = "median")
## S3 method for class 'wald'
print(x,...)
object |
Object of class |
splitcr |
Split criterion for subject raw score splitting. |
x |
Object of class |
... |
Further arguments passed to or from other methods. They are ignored in this function. |
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.
If the data set contains missing values and mean
or median
is specified as splitcriterion,
means or medians are calculated for each missing value subgroup and consequently used for raw score splitting.
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 |
se.beta2 |
Standard errors for second subgroup |
spl.gr |
Names and levels for |
call |
The matched call. |
Patrick Mair, Reinhold Hatzinger
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.
#Wald test for Rasch model with user-defined subject split
res <- RM(raschdat2)
splitvec <- sample(1:2,25,replace=TRUE)
Waldtest(res, splitcr = splitvec)