Permutation tests from biased samples for the equality of two distributions

Qing Kang and Paul Nelson

Journal of Nonparametric Statistics, 2009, vol. 21, issue 3, 305-319

Abstract: Suppose that independent samples are taken from two distributions according to two biased (nonrandom) sampling plans. This study constructs a class of biased-adjusted permutation tests for the equality of the two distributions. A resampling algorithm that generates permutations with unequal probabilities is proposed to estimate the tests’ exact P-values with a manageable Monte Carlo simulation error. This algorithm leads to the derivation of large-sample, normal theory tests. Conditions under which these tests are consistent are given. The tests’ power at finite sample sizes is examined via a simulation study.

Date: 2009
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DOI: 10.1080/10485250802617617

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