22 citations · 66 across the 22 of their papers we have counts for
6 papers · 2 filters
Efficient and robust methods for causally interpretable meta-analysis: transporting inferences from multiple randomized trials to a target population
Issa J. Dahabreh, Sarah E. Robertson, Lucia C. Petito +2
We present methods for causally interpretable meta-analyses that combine information from multiple randomized trials to estimate potential (counterfactual) outcome means and averag…
Generalizing causal inferences from randomized trials: counterfactual and graphical identification
Issa J. Dahabreh, James M. Robins, Sebastien J-P. A. Haneuse +1
When engagement with a randomized trial is driven by factors that affect the outcome or when trial engagement directly affects the outcome independent of treatment, the average tre…
Sensitivity analysis using bias functions for studies extending inferences from a randomized trial to a target population
Issa J. Dahabreh, James M. Robins, Sebastien J-P. A. Haneuse +4
Extending (generalizing or transporting) causal inferences from a randomized trial to a target population requires ``generalizability'' or ``transportability'' assumptions, which s…
Study designs for extending causal inferences from a randomized trial to a target population
Issa J. Dahabreh, Sebastien J-P. A. Haneuse, James M. Robins +4
We examine study designs for extending (generalizing or transporting) causal inferences from a randomized trial to a target population. Specifically, we consider nested trial desig…
Generalizing trial findings using nested trial designs with sub-sampling of non-randomized individuals
Issa J. Dahabreh, Miguel A. Hernan, Sarah E. Robertson +2
To generalize inferences from a randomized trial to the target population of all trial-eligible individuals, investigators can use nested trial designs, where the randomized indivi…
Towards causally interpretable meta-analysis: transporting inferences from multiple studies to a target population
Issa J. Dahabreh, Lucia C. Petito, Sarah E. Robertson +2
We take steps towards causally interpretable meta-analysis by describing methods for transporting causal inferences from a collection of randomized trials to a new target populatio…