From the 1 of 11 linked papers with an AI index.
11 papers
Towards Best Practices for Covariate Adjustment in Regulatory Trials: From Fixed to Data-Adaptive Approaches
Laura B. Balzer, Lei Nie, Issa J. Dahabreh +15
The paper discusses how to improve precision in randomized clinical trials by using covariate adjustment, comparing traditional fixed parametric methods with flexible data‑adaptive…
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…
Identification strategies for combining an experimental study with external data
Lawson Ung, Guanbo Wang, Sebastien Haneuse +2
There is increasing interest in combining information from experimental studies, including randomized and single-group trials, with information from external experimental or observ…
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…