title: A simple method for analyzing matched designs with double controls: McNemar's test can be extended.
abstract: 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 one-to-two matching (instead of one-to-one matching) when evaluating binary predictors and outcomes.
  
  
  
  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.
  
  
  
  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 handheld calculator. We further validate the approach by conducting simulations when a positive association was predefined and when a null association was predefined.
  
  
  
  The new approach provides a feasible, simple, and efficient method for analyzing matched designs with double controls.
authors: Department of Medicine, University of Toronto, Toronto, Ontario, Canada; Evaluative Clinical Sciences Program, Sunnybrook Research Institute, Toronto, Ontario, Canada; Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; Division of General Internal Medicine, Sunnybrook Health Sciences Centre, G-151, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada; Center for Leading Injury Prevention Practice Education & Research, Toronto, Ontario, Canada. Electronic address: dar@ices.on.ca.
authors: Donald A
authors: DA
authors: Redelmeier
authors: Department of Statistics, Stanford University, Stanford, CA, USA.
authors: Robert J
authors: RJ
authors: Tibshirani
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D016555:Matched-Pair Analysis; D015233:Models, Statistical
keywords: Case-only design; Crossover study; Matched pairs; Risk perception; Self-matching; Traffic accident