22 citations · 92 across the 25 of their papers we have counts for
10 papers · 1 filter
Generalizing and transporting inferences about the effects of treatment assignment subject to non-adherence
Issa J. Dahabreh, Sarah E. Robertson, Miguel A. Hernán
We discuss the identifiability of causal estimands for generalizability and transportability analyses, both under perfect and imperfect adherence to treatment assignment. We consid…
Robust Estimation of Loss-Based Measures of Model Performance under Covariate Shift
Samantha Morrison, Constantine Gatsonis, Issa J. Dahabreh +2
We present methods for estimating loss-based measures of the performance of a prediction model in a target population that differs from the source population in which the model was…
Selection on treatment in the target population of generalizabillity and transportability analyses
Yu-Han Chiu, Issa J. Dahabreh
Investigators are increasingly using novel methods for extending (generalizing or transporting) causal inferences from a trial to a target population. In many generalizability and…
Tree-based Subgroup Discovery In Electronic Health Records: Heterogeneity of Treatment Effects for DTG-containing Therapies
Jiabei Yang, Ann W. Mwangi, Rami Kantor +5
The rich longitudinal individual level data available from electronic health records (EHRs) can be used to examine treatment effect heterogeneity. However, estimating treatment eff…
Global sensitivity analysis for studies extending inferences from a randomized trial to a target population
Issa J. Dahabreh, James M. Robins, Sebastien J-P. A. Haneuse +3
When individuals participating in a randomized trial differ with respect to the distribution of effect modifiers compared compared with the target population where the trial result…
Systematically Missing Data in Causally Interpretable Meta-Analysis
Jon A. Steingrimsson, David H. Barker, Ruofan Bie +1
Causally interpretable meta-analysis combines information from a collection of randomized controlled trials to estimate treatment effects in a target population in which experiment…
Cluster randomized trials designed to support generalizable inferences
Sarah E. Robertson, Jon A. Steingrimsson, Issa J. Dahabreh
Background: When planning a cluster randomized trial, evaluators often have access to an enumerated cohort representing the target population of clusters. Practicalities of conduct…
Randomized trials and their observational emulations: a framework for benchmarking and joint analysis
Issa J. Dahabreh, Jon A. Steingrimsson, James M. Robins +1
A randomized trial and an analysis of observational data designed to emulate the trial sample observations separately, but have the same eligibility criteria, collect information o…
Extending inferences from a cluster randomized trial to a target population
Issa J. Dahabreh, Sarah E. Robertson, Jon A. Steingrimsson +2
We describe methods that extend (generalize or transport) causal inferences from cluster randomized trials to a target population of clusters, under a general nonparametric model t…
Learning about treatment effects in a new target population under transportability assumptions for relative effect measures
Issa J. Dahabreh, Sarah E. Robertson, Jon A. Steingrimsson
Epidemiologists and applied statisticians often believe that relative effect measures conditional on covariates, such as risk ratios and mean ratios, are ``transportable'' across p…