Matched cohort analysis in traffic injury epidemiology: including adults when estimating exposure risks for children

Injury Prevention : Journal of the International Society for Child and Adolescent Injury Prevention
Michael R Elliott

Abstract

Matched cohort analyses and their extension to conditional logistic and Poisson regression are powerful tools for assessing risk and protective factors in automobile crashes. However, these analyses rely on assumptions about latent (unobserved) 'crash severity' risk measures for subjects in the vehicle being common for all such subjects if confounding with crash severity is present. The assumptions may be questionable if adults are being matched to children. Simulations were conducted to evaluate conditional Poisson regression in settings where different types of subjects may have different underlying baseline summary risk measures in a given crash-for example, adults and children. Situations were considered where baseline summary risk measures and protective factors are confounded with each other and where the adult and child baseline risk measures are either highly correlated or weakly correlated. When the risk or protective factor is confounded with crash severity, baseline summary risk measures due to crash severity must be perfectly correlated for all subjects in the crash for the factor to be consistently estimated. Relative bias estimates ranged from 5% to 50% depending on the degree of correlation of the risk measure an...Continue Reading

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