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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
On the efficiency of bootstrap method into the analysis contingency table
Saeid Amiri1, Dietrich von Rosen
1Department of Mathematics, Uppsala University, PO Box 480, 751 06 Uppsala, Sweden. saeid.amiri1@gmail.com
Abstract:
The bootstrap method is a computer intensive statistical method that is widely used in performing nonparametric inference. Categorical data analysis, in particular the analysis of contingency tables, is commonly used in applied field. This work considers nonparametric bootstrap tests for the analysis of contingency tables. There are only a few research papers which exploit this field. The p-values of tests in contingency tables are discrete and should be uniformly distributed under the null hypothesis. The results of this article show that corresponding bootstrap versions work better than the standard tests. Properties of the proposed tests are illustrated and discussed using Monte Carlo simulations. This article concludes with an analytical example that examines the performance of the proposed tests and the confidence interval of the association coefficient.
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