3 citations · 10 across the 6 of their papers we have counts for
4 papers · 1 filter
Real Effect or Bias? Best Practices for Evaluating the Robustness of Real-World Evidence through Quantitative Sensitivity Analysis for Unmeasured Confounding
Douglas Faries, Chenyin Gao, Xiang Zhang +7
The assumption of no unmeasured confounders is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of re…
Bayesian Record Linkage with Variables in One File
Gauri Kamat, Mingyang Shan, Roee Gutman
In many healthcare and social science applications, information about units is dispersed across multiple data files. Linking records across files is necessary to estimate the assoc…
Sensitivity Analysis for Unmeasured Confounding in Medical Product Development and Evaluation Using Real World Evidence
Yixin Fang, Pallavi Mishra-Kalyani, Xiang Zhang +8
The American Statistical Association Biopharmaceutical Section (ASA BIOP) scientific working group on real-world evidence (RWE) has been making continuous, extended efforts towards…
Improving randomized controlled trial analysis via data-adaptive borrowing
Chenyin Gao, Shu Yang, Mingyang Shan +3
In recent years, real-world external controls have grown in popularity as a tool to empower randomized placebo-controlled trials, particularly in rare diseases or cases where balan…