A test of independence in two-way contingency tables based on maximal correlation

Date
2011
Authors
Yenigün, C. D.
Székely, G. J.
Rizzo, M. L.
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Source Title
Communications in Statistics - Theory and Methods
Print ISSN
0361-0926
Electronic ISSN
Publisher
Taylor & Francis
Volume
40
Issue
12
Pages
2225 - 2242
Language
English
Type
Article
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Abstract

Maximal correlation has several desirable properties as a measure of dependence, including the fact that it vanishes if and only if the variables are independent. Except for a few special cases, it is hard to evaluate maximal correlation explicitly. We focus on two-dimensional contingency tables and discuss a procedure for estimating maximal correlation, which we use for constructing a test of independence. We compare the maximal correlation test with other tests of independence by Monte Carlo simulations. When the underlying continuous variables are dependent but uncorrelated, we point out some cases for which the new test is more powerful.

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Keywords
Exact tests, Maximal correlation, Tests of independence, Contingency table, Continuous variables, Exact tests, Maximal correlation, Monte Carlo Simulation, Tests of independence, Computer simulation, Correlation methods, Monte Carlo methods, Testing
Citation
Published Version (Please cite this version)