Analysis of clustered matched-pair data
Article first published online: 14 JUL 2003
Copyright © 2003 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 22, Issue 15, pages 2417–2428, 15 August 2003
How to Cite
Durkalski, V. L., Palesch, Y. Y., Lipsitz, S. R. and Rust, P. F. (2003), Analysis of clustered matched-pair data. Statist. Med., 22: 2417–2428. doi: 10.1002/sim.1438
- Issue published online: 14 JUL 2003
- Article first published online: 14 JUL 2003
- Manuscript Accepted: SEP 2002
- Manuscript Received: JUL 2001
- clustered binary data;
- diagnostic testing;
- McNemar test
Evaluation of the performance of a new diagnostic procedure with respect to a standard procedure arises frequently in practice. The response of interest, often in a dichotomous form, is measured twice, once with each procedure. The two procedures are administered to either two matched individuals, or when practical, to the same individual. A large sample test for matched-pair data is the McNemar test. The main assumption of this test is independent paired responses; however, when more than one outcome from an individual is measured by each procedure, the data are clustered. Examples of such cases can be seen in dental and ophthalmology studies. Variance adjustment methods for the analysis of clustered matched-pair data have been proposed; however, because of unequal cluster sizes, variability of correlation structures within a cluster (within paired responses in a cluster as well as between paired responses in a cluster), and unequal success probabilities among the clusters, the performances of some available methods are not consistent. This research proposes a simple adjustment to the McNemar test for the analysis of clustered matched-pair data. Method of moments is used to calculate a consistent variance estimator. Using Monte Carlo simulation, the size and power of the proposed test are compared to those of two currently available methods. To illustrate practical application, clustered matched-pair data from two clinical studies are analysed. Copyright © 2003 John Wiley & Sons, Ltd.