Simultaneous Modeling of Multiple Binary Outcomes: A GEE Approach

• Activity Number: 175
• Type: Contributed
• Date/Time: Tuesday, August 13, 2002 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology*
• Author(s): Abhik Das*+ and W. Poole and Henrietta Bada
• Affiliation(s): RTI International and RTI International and University of Kentucky
• Keywords: multiple binary outcomes ; syndrome ; GEE ; multiple comparisons ; simultaneous modeling ; outcome-specific effects

Abstract

Multiple binary outcomes are frequently encountered in epidemiologic research. This work was motivated by the Maternal Lifestyle Study, where newborns prenatally exposed to cocaine and a comparison cohort, were examined for the presence of autonomic and central nervous system (ANS/CNS) signs. Thus, each infant contributed to multiple, possibly interrelated, binary outcomes that may collectively constitute one syndrome (even though specific outcomes that are affected by cocaine are of scientific interest). Since it is neither scientifically appropriate nor statistically efficient to fit separate models for each outcome, here we adopt a multivariate GEE approach to simultaneously model all the ANS/CNS outcomes as a function of cocaine exposure and other covariates. This formulation has a number of advantages. First, it implicitly recognizes that all the ANS/CNS outcomes may together constitute one syndrome. Second, simultaneous modeling boosts statistical efficiency by allowing for correlations among the outcomes and avoids multiple comparisons. Third, it allows for outcome-specific exposure effects, so that we can identify the specific signs that are affected by cocaine exposure.