von Rosen, Dietrich
- Institutionen för energi och teknik, Sveriges lantbruksuniversitet
Sammanfattning
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. (C) 2011 Elsevier Ireland Ltd. All rights reserved.
Nyckelord
Association coefficient; Bootstrap method; Chi-squared test; Contingency table; Monte Carlo simulation
Publicerad i
Computer Methods and Programs in Biomedicine
2011, volym: 104, nummer: 2, sidor: 182-187
Utgivare: ELSEVIER IRELAND LTD
SLU författare
UKÄ forskningsämne
Datavetenskap (datalogi)
Publikationens identifierare
- DOI: https://doi.org/10.1016/j.cmpb.2011.01.007
Permanent länk till denna sida (URI)
https://res.slu.se/id/publ/46177