.png){kind=icon}
Return
Proximal indirect comparison
.png){kind=icon}
PRE
AI
DOI：10.1093/biomet/asaf044.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We consider the problem of indirect comparison, where a treatment arm of interest is absent by design in one randomized controlled trial, but available in the other. The former is the target trial, and the latter is the source trial. The identifiability of the target population average treatment effect often relies on conditional transportability assumptions. However, it is a common concern whether all relevant effect modifiers are measured and controlled for. We give a new proximal identification result in the presence of shifted, unobserved effect modifiers based on proxies: an adjustment proxy in both trials and an additional reweighting proxy in the source trial. We propose an estimator that is doubly robust against misspecifications of the so-called bridge functions and asymptotically normal under mild consistency of estimators for the bridge functions. We use two weight management trials as a context to illustrate selection of proxies and apply our method to compare the weight loss effect of active treatments from these trials.
Keywords:
Indirect comparison
Meta-analysis
Proximal causal inference
Transportability
Journal
B
IF:
2.8
Papers:
34
Citations:
0
Organization
Cited Papers
ShareSaveCausal Inference Methods for Combining Randomized Trials and Observational Studies: A Review.png)
STATISTICAL SCIENCE
OAAI
STATISTICAL SCIENCEIF3.4
OAAIShareSaveShareSaveShareSaveImpact of social determinants of health on outcomes for type 2 diabetes: a systematic reviewENDOCRINEOAAI
ENDOCRINEIF2.9
OAAIShareSave
View more