Causally interpretable meta-analysis: Transporting inferences from multiple randomized trials to a target population

We will argue that currently popular methods for meta-analysis do not produce estimates with a clear causal interpretation. We will propose novel methods for causally interpretable meta-analyses that combine information from multiple randomized trials to draw inferences about treatment effects in a well-defined target population of substantive interest. We will use theoretical arguments, simulations and an empirical evaluation to examine the performance of the proposed methods. Last, we will attempt to identify some areas for future research.

Speaker: Issa Dahabreh, MD, ScD, Associate Professor of Epidemiology, Harvard T.H. Chan, School of Public Health

To obtain Zoom link please email: Liz Buggs