@article{ref1,
title="A simple method for analyzing matched designs with double controls: McNemar's test can be extended",
journal="Journal of clinical epidemiology",
year="2016",
author="Redelmeier, Donald A. and Tibshirani, Robert J.",
volume="81",
number="",
pages="51-55.e2",
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. <br><br>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. <br><br>CONCLUSION: The new approach provides a feasible, simple, and efficient method for analyzing matched designs with double controls.<br><br>Copyright © 2016 Elsevier Inc. All rights reserved.<p /> <p>Language: en</p>",
language="en",
issn="0895-4356",
doi="10.1016/j.jclinepi.2016.08.006",
url="http://dx.doi.org/10.1016/j.jclinepi.2016.08.006"
}