A permutation test for nonindependent matched pair data

Seung ho Kang, Hyung W. Kim, Chul W. Ahn

Research output: Contribution to journalArticle

Abstract

The paired t-test and the Wilcoxon signed-rank test are often conducted to compare two continuous outcomes from paired observations. An assumption underlying these tests is that the responses from pair to pair are mutually independent. However, the assumption is violated in certain applications such as site-specific data in periodontal research. An adjustment to the paired t-test to account for the clustering effect has been well developed. But the adjustment relies on either large sample theory or the assumption that the observations being analyzed follow a normal distribution. In this paper, we propose a permutation test for matched pair clustered data which are valid in small samples. We developed and reviewed software to carry out the proposed test. The proposed test is applied to real-life data.

Original languageEnglish
Pages (from-to)407-411
Number of pages5
JournalTherapeutic Innovation & Regulatory Science
Volume35
Issue number2
DOIs
Publication statusPublished - 2001

All Science Journal Classification (ASJC) codes

  • Pharmacology, Toxicology and Pharmaceutics (miscellaneous)
  • Public Health, Environmental and Occupational Health
  • Pharmacology (medical)

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