Semiparametric clustered overdispersed multinomial goodness-of-fit of log-linear models
Methodology
2016-09-26 v1
Abstract
Traditionally, the Dirichlet-multinomial distribution has been recognized as a key model for contingency tables generated by cluster sampling schemes. There are, however, other possible distributions appropriate for these contingency tables. This paper introduces new test-statistics capable to test log-linear modeling hypotheses with no distributional specification, when the individuals of the clusters are possibly homogeneously correlated. The estimator for the intracluster correlation coefficient proposed in Alonso-Revenga et al. (2016), valid for different cluster sizes, plays a crucial role in the construction of the goodness-of-fit test-statistic.
Keywords
Cite
@article{arxiv.1609.07330,
title = {Semiparametric clustered overdispersed multinomial goodness-of-fit of log-linear models},
author = {Juana M. Alonso-Revenga and Nirian Martin and Leandro Pardo},
journal= {arXiv preprint arXiv:1609.07330},
year = {2016}
}