Authors

• Baojiang Chen
• Zhijian Chen
• Longyang Wu
• Lihua Wang
• Grace Y. Yi

Abstract

A common study to investigate gene-environment interaction
is designed to be longitudinal and population-based. Data arising
from longitudinal association studies often contain missing responses.
Naive analysis without taking missingness into account may produce
invalid inference, especially when the missing data mechanism depends
on the response process. To address this issue in the analysis concerning
gene-environment interaction effects, in this paper, we adopt an inverse
probability weighted generalized estimating equations (IPWGEE)
approach to conduct statistical inference. This approach is attractive
because it does not require full model specification yet it can provide
consistent estimates under the missing at random (MAR) mechanism.
We utilize this method to analyze data arising from a cardiovascular
disease study.

Keywords

• Generalized estimating equations
• Genetic Association
• longitudinal data
• missing at random