A statistical test for the equality of differently adjusted incidence rate ratios

Item Type:	Article
Title:	A statistical test for the equality of differently adjusted incidence rate ratios
Creators Name:	Hoffmann, K. and Pischon, T. and Schulz, M. and Schulze, M.B. and Ray, J. and Boeing, H.
Abstract:	An incidence rate ratio (IRR) is a meaningful effect measure in epidemiology if it is adjusted for all important confounders. For evaluation of the impact of adjustment, adjusted IRRs should be compared with crude IRRs. The aim of this methodological study was to present a statistical approach for testing the equality of adjusted and crude IRRs and to derive a confidence interval for the ratio of the two IRRs. The method can be extended to compare two differently adjusted IRRs and, thus, to evaluate the effect of additional adjustment. The method runs immediately on existing software. To illustrate the application of this approach, the authors studied adjusted IRRs for two risk factors of type 2 diabetes using data from the European Prospective Investigation into Cancer and Nutrition-Potsdam Study from 2005. The statistical method described may be helpful as an additional tool for analyzing epidemiologic cohort data and for interpreting results obtained from Cox regression models with adjustment for different covariates.
Keywords:	Cohort Studies, Confounding, Diabetes Mellitus, Type 2, Epidemiologic Methods, Proportional Hazards Models, Statistics
Source:	American journal of epidemiology
ISSN:	0002-9262
Publisher:	Oxford University Press
Volume:	167
Number:	5
Page Range:	517-522
Date:	1 March 2008
Official Publication:	https://doi.org/10.1093/aje/kwm357
PubMed:	View item in PubMed

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