A calibration approach to transportability and data-fusion with observational data.

ABSTRACT: Two important considerations in clinical research studies are proper evaluations of internal and external validity. While randomized clinical trials can overcome several threats to internal validity, they may be prone to poor external validity. Conversely, large prospective observational studies sampled from a broadly generalizable population may be externally valid, yet susceptible to threats to internal validity, particularly confounding. Thus, methods that address confounding and enhance transportability of study results across populations are essential for internally and externally valid causal inference, respectively. These issues persist for another problem closely related to transportability known as data-fusion. We develop a calibration method to generate balancing weights that add

SUBMITTER: Josey KP 

PROVIDER: S-EPMC10201931 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature