Assessing the ability of an instrumental variable causal forest algorithm to personalize treatment evidence using observational data: the case of early surgery for shoulder fracture

Assessing the ability of an instrumental variable causal forest algorithm to personalize treatment evidence using observational data: the case of early surgery for shoulder fracture

Abstract Background Comparative effectiveness research (CER) using observational databases has been suggested to obtain personalized evidence of treatment effectiveness. Inferential difficulties remain using traditional CER approaches especially related to designating patients to reference classes a...

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Bibliographic Details
Main Authors: John M. Brooks, Cole G. Chapman, Sarah B. Floyd, Brian K. Chen, Charles A. Thigpen, Michael Kissenberth
Format: Article
Language:English
Published: BMC 2022-07-01
Series:BMC Medical Research Methodology
Subjects:
Instrumental Variable Causal Forest Algorithm
Classification and regression trees (CART)
Two-stage least squares (2SLS) estimators
Proximal humerus fracture
Surgery
Online Access:https://doi.org/10.1186/s12874-022-01663-0

Internet

https://doi.org/10.1186/s12874-022-01663-0

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