Citation

Redelmeier DA, Tibshirani RJ. J. Clin. Epidemiol. 2016; 81: 51-55.e2.

Affiliation

Department of Statistics, Stanford University.

Copyright

(Copyright © 2016, Elsevier Publishing)

DOI

10.1016/j.jclinepi.2016.08.006

PMID

27565976

Abstract

OBJECTIVE: To introduce a new analytic approach for matched studies where exactly two controls are linked to each case (double controls rather than solitary controls). The intent is to extend McNemar's test for 1-to-2 matching (instead of 1-to-1 matching) when evaluating binary predictors and outcomes. STUDY DESIGN AND SETTING: We review McNemar's approach for analyzing matched data, demonstrate the Mantel-Haenszel approach for integrating two overlapping McNemar's estimates, review conditional logistic regression as an alternative analytic approach, and introduce a new method that yields a visual display and easy verification.

RESULTS: We illustrate the new approach with real data testing the association between overcast weather and the risk of a life-threatening traffic crash (n = 6,962). We show that results from the new approach agree closely with conditional logistic regression and are sufficiently simple as to be computed on a hand-held calculator. We further validate the approach by conducting simulations when a positive association was pre-defined and when a null association was pre-defined.

CONCLUSION: The new approach provides a feasible, simple, and efficient method for analyzing matched designs with double controls.

Copyright © 2016 Elsevier Inc. All rights reserved.

Language: en