The Parametric G-Formula for Comparative Effectiveness Research

• Activity Number: 384
• Type: Invited
• Date/Time: Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
• Sponsor: International Chinese Statistical Association
• Author(s): Miguel A. Hernán*+
• Companies: Harvard School of Public Health
• Keywords: g-formula ; observational studies ; comparative effectiveness research

Abstract

The increasing availability of complex longitudinal databases presents both challenges and opportunities for comparative effectiveness research. A key challenge is the implementation of statistical methods that can (1) compare clinically relevant dynamic regimes, and (2) appropriately adjust for measured time-varying confounding and selection bias. Semiparametric methods such as inverse probability weighting of marginal structural models and g-estimation of nested structural models can be used to achieve these goals. However, these methods do not easily accommodate some classes of dynamic regimes, and semiparametric estimates may have a large variance when obtained from many currently available databases. A fully-parametric alternative to these methods is the parametric g-formula. Though first proposed by Robins in 1986, the g-formula has been little used in practice, and thus its relevance for comparative effectiveness research remains largely unexplored. This presentation discusses recent refinements, software developments, and practical implementations of the parametric g-formula.