MLoef | R Documentation |
This Likelihood-Ratio-Test is based on item subgroup splitting.
MLoef(robj, splitcr = "median")
robj |
An object of class |
splitcr |
Split criterion to define the item groups.
|
This function implements a generalization of the Martin-Löf test for polytomous items as proposed by Christensen, Bjørner, Kreiner & Petersen (2002), but does currently not allow for missing values.
If the split criterion is "median"
or "mean"
and one or more items' raw scores are equal the median resp. mean, MLoef
will assign those items to the lower raw score group.
summary.MLoef
gives detailed information about the allocation of all items.
summary
and print
methods are available for objects of class 'MLoef'
.
An ‘exact’ version of the Martin-Löf test for binary items is implemented in the NPtest
function.
MLoef
returns an object of class MLoef
containing:
LR |
LR-value |
df |
degrees of freedom |
p.value |
p-value of the test |
fullModel |
the overall Rasch model |
subModels |
a list containing the submodels |
Lf |
log-likelihood of the full model |
Ls |
list of the sub models' log-likelihoods |
i.groups |
a list of the item groups |
splitcr |
submitted split criterion |
split.vector |
binary allocation of items to groups |
warning |
items equalling median or mean for the respective split criteria |
call |
the matched call |
Marco J. Maier, Reinhold Hatzinger
Christensen, K. B., Bjørner, J. B., Kreiner S. & Petersen J. H. (2002). Testing unidimensionality in polytomous Rasch models. Psychometrika, (67)4, 563–574.
Fischer, G. H., and Molenaar, I. (1995). Rasch Models – Foundations, Recent Developements, and Applications. Springer.
Rost, J. (2004). Lehrbuch Testtheorie – Testkonstruktion. Bern: Huber.
LRtest
, Waldtest
# Martin-Löf-test on dichotomous Rasch model using "median" and a user-defined
# split vector. Note that group indicators can be of character and/or numeric.
splitvec <- c(1, 1, 1, "x", "x", "x", 0, 0, 1, 0)
res <- RM(raschdat1[,1:10])
MLoef.1 <- MLoef(res, splitcr = "median")
MLoef.2 <- MLoef(res, splitcr = splitvec)
MLoef.1
summary(MLoef.2)
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