Measurement Error Correction in Exploiting Gene-Environment Independence in Family-Based Case-Control Studies.

Family-based case-control designs are commonly used in epidemiological studies for evaluating the role of genetic susceptibility and environmental exposure to risk factors in the etiology of rare diseases. Within this framework, it is often reasonable to assume genetic susceptibility and environmental exposure being conditionally independent of each other within families in the source population. We focus on this setting to consider the common situation of measurement error aecting the assessment of the environmental exposure. We propose to correct for measurement error through a likelihood-based method, by exploiting the conditional likelihood of Chatterjee, Kalaylioglu and Carroll (2005) to relate the probability of disease to the genetic and the mismeasured environmental risk factors. Simulation studies show that this approach provides less biased and more ecient results than that based on traditional logistic regression. The likelihood approach for measurement error correction is also compared to regression calibration, the last resulting in severely biased estimators of the parameters of interest