164 citations · 180 across the 14 of their papers we have counts for
9 papers · 1 filter
Estimand frameworks for causal inference in clinical research and regulatory decision making
Miguel A. Hernán, Mats J. Stensrud, Xabier García-Albéniz +2
Causal inference for clinical and regulatory decision making requires a precise definition of the causal estimand, that is, what we want to estimate. Three frameworks are commonly…
Comparing randomized trials
Yu-Han Chiu, Issa J. Dahabreh
Disagreements between randomized trials that address the same causal question pose challenges for the interpretation and synthesis of evidence. We sketch a causal framework for com…
Transportability methods for failure-time outcomes under assumptions for relative effect measures
Sarah E Robertson, Lan Wen, Lawson Ung +2
In certain clinical areas, relative effect measures are believed to remain more constant across populations than absolute measures. This suggests that exchangeability assumptions o…
Towards Best Practices for Covariate Adjustment in Regulatory Trials: From Fixed to Data-Adaptive Approaches
Laura B. Balzer, Lei Nie, Issa J. Dahabreh +15
While randomization justifies the use of unadjusted effect estimators in randomized trials, there is growing interest in covariate adjustment to improve precision. Adjusting for ba…
Causally-interpretable meta-analysis using aggregate data
Qingyang Shi, Wouter van Amsterdam, Sacha la Bastide-van Gemert +2
Evidence syntheses and meta-analyses are used to inform clinical practice guidelines and health economic evaluations. However, heterogeneity of treatment effects poses a significan…
Using the target trial framework for combining information: external comparator analyses and other applications
Lawson Ung, Miguel A. Hernán, Issa J. Dahabreh
We describe how the target trial framework can be used to plan and report analyses that attempt to answer causal questions by combining information from multiple, diverse sources.…
Generalizing conditional average treatment effects from nested randomized trials to all trial-eligible individuals
Lan Wen, Issa J. Dahabreh, Yu-Han Chiu
Randomized controlled trials often enroll participants whose characteristics differ from those of a target population, which can limit the generalizability of the estimated treatme…
Constructing external comparator groups via transportability in mean or in effect measure
Lawson Ung, Guanbo Wang, Sebastien Haneuse +3
Learning about causal effects in target populations and their subsets may be facilitated by combining information from multiple sources. One major class of study designs that combi…
Considerations for the Integration of Randomized Controlled Trials and Real-World Data
Sky Qiu, Charles Barr, Lauren Dang +18
As clinical decision-making increasingly moves toward individualized and context-specific treatment recommendations, reliance on any single evidence source, randomized or observati…