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

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      Author
      Yenigün, C. D.
      Székely, G. J.
      Rizzo, M. L.
      Date
      2011
      Source Title
      Communications in Statistics - Theory and Methods
      Print ISSN
      0361-0926
      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.
      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
      Permalink
      http://hdl.handle.net/11693/22060
      Published Version (Please cite this version)
      http://dx.doi.org/10.1080/03610921003764274
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