Non-inferiority tests for clustered matched-pair data

Jun Mo Nam, Deukwoo Kwon

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Non-inferiority tests for matched-pair data where pairs are mutually independent may not be appropriate when pairs are clustered. The tests may require an adjustment to account for the correlation within a cluster. We consider the adjusted score and Wald-type tests, and a modification of Obuchowski's method for non-inferiority and compare them with the non-inferiority test based on a method of moments estimate in terms of Type 1 error rate and power by simulations for a small cluster size under various correlation structures. In general, the score test adjusted by an inflation factor and the modified Obuchowski's method perform as good as the test based on moments estimate in the accuracy of Type 1 error rates. The latter does not provide reasonably close Type 1 error rates to the nominal level when the number of clusters is 25 or smaller and a positive response rate for the standard procedure is 20 per cent or lower. The adjusted score test, the method based on moments estimate and the modified test are comparable in power. The adjusted Wald-type test is too anti-conservative and we should caution use of the test. Since number of clusters is strongly related to the accuracy of empirical Type 1 error rate and power, it is very important to have a sufficiently large number of clusters in designing a clustered matched-pair study for non-inferiority.

Original languageEnglish (US)
Pages (from-to)1668-1679
Number of pages12
JournalStatistics in Medicine
Volume28
Issue number12
DOIs
StatePublished - May 30 2009
Externally publishedYes

Keywords

  • Adjusted score test
  • Adjusted Wald-type test
  • Clustered matched pair
  • Method of moments estimate
  • Non-inferiority

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

Fingerprint

Dive into the research topics of 'Non-inferiority tests for clustered matched-pair data'. Together they form a unique fingerprint.

Cite this