WITHDRAWN: On the Shape of an Exposure-Disease Relationship, the Average Effect of Exposure, and the Impact of Exposure Measurement Error

• Activity Number: 603
• Type: Contributed
• Date/Time: Wednesday, August 12, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Li Xing and Paul Gustafson and Igor Burstyn
• Companies: Indiana University and The University of British Columbia and Drexel University
• Keywords: Shape of the Exposure-Disease Relationship ; Average Predictive Effect ; Measurement Error ; Misspecified Model ; Logistic Box-Cox Model

Abstract

The shape of the relationship between a continuous exposure variable and a binary disease variable is often central to epidemiologic investigations. This paper investigates a number of issues surrounding inference and the shape of the relationship. Presuming that the relationship can be expressed in terms of regression coefficients and a shape parameter, we investigate how well the shape can be inferred in settings which might typify epidemiologic investigations and risk assessment. We also consider a suitable definition of the average effect of exposure, and investigate how precisely this can be inferred. This is done both in the case of using a model acknowledging uncertainty about the shape parameter and in the case of using a simple model ignoring this uncertainty. We also examine the extent to which exposure measurement error distorts inference about the shape of the exposure- disease relationship. All these investigations require a family of exposure-disease relationships indexed by a shape parameter. For this purpose, we employ a family based on the Box-Cox transformation