Limited Information Goodness-Of-Fit Testing In Multidimensional Contingency Tables
We introduce a family of goodness-of-fit statistics for testing composite null hypotheses in multidimensional contingency tables of arbitrary dimensions. These statistics are quadratic forms in marginal residuals up to order r. They are asymptotically chi-square under the null hypothesis when parameters are estimated using any consistent and asymptotically normal estimator. We show that when r is small (r = 2) the proposed statistics have more accurate empirical Type I errors and are more powerful than Pearson´s X2 for a widely used item response model. Also, we show that the proposed statistics are asymptotically chi-squared under the null hypothesis when applied to subtables.
Year of publication: |
2005-02
|
---|---|
Authors: | MAYDEU, ALBERTO |
Institutions: | Área de Entorno Económico, Instituto de Empresa |
Saved in:
freely available
Saved in favorites
Similar items by person
-
Asymptotically distribution free (adf) interval estimation of coefficient alpha
MAYDEU, ALBERTO, (2006)
-
Limited and full information estimation and goodness-of-fit testing in 2n contingency tables
MAYDEU, ALBERTO, (2003)
-
Entrepreneurial activity and entrepreneurial environment? A reexamination of the GEM´s approach
CASTRO, JULIO ORLANDO DE, (2005)
- More ...