A test of independence in two-way contingency tables based on maximal correlation
Author
Yenigün, C. D.
Székely, G. J.
Rizzo, M. L.
Date
2011Source Title
Communications in Statistics - Theory and Methods
Print ISSN
0361-0926
Publisher
Taylor & Francis
Volume
40
Issue
12
Pages
2225 - 2242
Language
English
Type
ArticleItem Usage Stats
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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.
Keywords
Exact testsMaximal 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