“Targeted Learning in the SEARCH Trial and HIV Prevention in East Africa” with Laura Balzer, Harvard
QUANTITATIVE RESEARCH METHODS WORKSHOP
Abstract: Evaluation of cluster-based interventions presents significant methodological challenges. In this talk, we describe the design and analysis of the SEARCH trial, an ongoing community randomized trial to evaluate the impact of early HIV diagnosis and immediate treatment with streamlined care in rural Uganda and Kenya. We focus on 3 choices to optimize the design and analysis: pair-matching over complete randomization, targeting the sample effect instead of a population average parameter, and data-adaptive adjustment through a pre-specified targeted maximum likelihood estimator (TMLE). These choices are compared theoretically and with finite sample simulations. We demonstrate each choice improves efficiency relative to standard practice, while maintaining nominal confidence interval coverage. We conclude with practical implications and some ongoing challenges.
Dr. Laura Balzer, PhD MPhil, is a post-doctoral fellow in the Biostatistics Department at the Harvard T.H. Chan School of Public Health. She earned her PhD in Biostatistics from the University of California, Berkeley. Laura is a methodologist with substantive interests in global health, community-based participatory research, and social determinants of health. Her particular areas of expertise are Causal Inference and Implementation Science. Laura is also passionate about teaching introductory and advanced causal and statistical methods. Jointly with Dr. Maya Petersen, she was awarded the 2014 ASA’s Causality in Statistics Education Award.