Beschreibung
The dichotomous Rasch-model (Rasch, 1960) is an Item Response model, where the validation is commonlyrelated to the use of big sample sizes. But, in the phase of design of a psychological test, the examination of items by means of a large sample of persons is not always efficient, e.g., reanalyzing the items by means of a new sample is associated with high costs. It would be preferable to test the items stepwise with small samples but based on few subjects, as the estimation of the parameters is problematic and parametric model checks have little power. Ponocny (2001) introduced nonparametric (exact) test procedures based on Monte-Carlo simulations to sample random matrices with the same marginals as the observed data matrix. His simulation method
and proposed test-statistics allow to check the model fit even in small samples. Verhelst (2008) improved the
simulation algorithm using a Markov-Chain Monte-Carlo (MCMC) approach. Recently, some test statistics and
the MCMC method have been implemented in the R packages RaschSampler (Verhelst, Hatzinger &, Mair, 2007) and eRm (Mair & Hatzinger, 1997) In this presentation we describe some test statistics and give an overview
of first results of a power-analysis comparing the nonparametric tests with the likelihood ratio test 26
(LRT)according to Andersen (1973). A practical application demonstrates the usefulness of the nonparametric
methods.
| Zeitraum | 16 Sept. 2010 → 18 Sept. 2010 |
|---|---|
| Ereignistitel | 9th Alps-Adria Psychology Conference |
| Veranstaltungstyp | Keine Angaben |
| Bekanntheitsgrad | National |