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Exact conditional tests for incomplete contingency tables: estimating attained significance levels

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Abstract

A Monte Carlo exact conditional test of quasi-independence in two-way incomplete contingency tables is proposed. The null distribution of a random table under quasiindependence is derived. This distribution depends only on the counts in the cells of interest and not on the counts in the remaining cells. This result is used to improve the efficiency of a proposed simulate-and-reject Monte Carlo procedure for estimating the attained significance level.

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Authors and Affiliations

  1. Department of Social Statistics, University of Southampton, 17 1BJ, Southampton, SO, UK

    Peter W. F. Smith & John W. McDonald

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  1. Peter W. F. Smith
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  2. John W. McDonald
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Smith, P.W.F., McDonald, J.W. Exact conditional tests for incomplete contingency tables: estimating attained significance levels. Stat Comput 5, 253–256 (1995). https://doi.org/10.1007/BF00142667

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