In this article the problem of comparing distributional heterogeneities for categorical variables is addressed. Specifically, the one-sided testing problem for heterogeneity comparisons is considered. For such a problem a bootstrap method is proposed and compared with a permutation method already present in literature. The power behavior of the two methods is compared through a Monte Carlo simulation study. The results of two real applications are shown.
Testing for Heterogeneity with Categorical Data: Permutation Solution vs. Bootstrap Method
BONNINI, Stefano
2014
Abstract
In this article the problem of comparing distributional heterogeneities for categorical variables is addressed. Specifically, the one-sided testing problem for heterogeneity comparisons is considered. For such a problem a bootstrap method is proposed and compared with a permutation method already present in literature. The power behavior of the two methods is compared through a Monte Carlo simulation study. The results of two real applications are shown.File in questo prodotto:
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