Citation

Redelmeier DA, Tibshirani RJ. J. Clin. Epidemiol. 2018; 98: 117-122.

Affiliation

Department of Biomedical Data Sciences, Stanford University; Department of Statistics, Stanford University.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.jclinepi.2018.02.005

PMID

29452220

Abstract

OBJECTIVE: To demonstrate analytic approaches for matched studies where two controls are linked to each case and events are accumulating counts rather than binary outcomes. A secondary intent is to clarify the distinction between total risk and excess risk (unmatched vs matched perspectives). STUDY DESIGN AND SETTING: We review past research testing whether elections can lead to increased traffic risks. The results are reinterpreted by analyzing both the total count of individuals in fatal crashes and the excess count of individuals in fatal crashes, each time accounting for the matched double controls.

RESULTS: Overall, 1,546 individuals were in fatal crashes on the 10 election days (average = 155 per day) and 2,593 individuals were in fatal crashes on the 20 control days (average = 130 per day). Poisson regression of total counts yielded a relative risk of 1.19 (95% confidence interval 1.12 to 1.27). Poisson regression of excess counts yielded a relative risk of 3.22 (95% confidence interval 2.72 to 3.80). The discrepancy between analyses of total counts and excess counts replicated with alternative statistical models and was visualized in graphical displays.

CONCLUSION: Available approaches provide methods for analyzing count data in matched designs with double controls and help clarify the distinction between increases in total risk and increases in excess risk.

Copyright © 2018 Elsevier Inc. All rights reserved.

Language: en

Keywords

Case only design; Crossover study; Matched pairs; Minimization of bias; Presidential election; Risk perception; Self-matching