Doubly robust estimation of attributable fractions.
The attributable fraction (AF) is a widely used measure to assess the impact of an exposure on a disease. It is commonly estimated through maximum likelihood, which requires a regression model for the outcome. Recently, it was demonstrated that the AF can also be estimated through inverse probability weighting, which requires a model for the exposure. In this paper, we derive doubly robust estimators for the AF. These estimators require one model for the outcome and one model for the exposure and are consistent if either model is correct, not necessarily both. We consider both cohort/cross-sectional studies and case-control studies.
Sjölander
Arvid
A
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden. arvid.sjolander@ki.se
Vansteelandt
Stijn
S
D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000209:etiology; D016022:Case-Control Studies; D015331:Cohort Studies; D003198:Computer Simulation; D003430:Cross-Sectional Studies; D016021:Epidemiologic Studies; D006801:Humans; D008175:Lung Neoplasms / Q000209:etiology; D015233:Models, Statistical; D012044:Regression Analysis; D012907:Smoking