Open AccessLetter to the Editor: Pulling Unmeasured Confounding Out by your Bootstraps: Too Good to be True?
Author(s) -
Corentin Ségalas,
Clémence Leyrat,
Elizabeth Williamson
Publication year - 2022
Publication title -
journal of statistical research
Language(s) - English
Resource type - Journals
ISSN - 0256-422X
DOI - 10.3329/jsr.v55i2.58806
Subject(s) - confounding , weighting , statistics , econometrics , computer science , mathematics , medicine , radiology
Inverse probability of treatment weighting can account for confounding under a number of assumptions, including that of no unmeasured confounding. A recent simulation study proposed a bootstrap bias correction, apparently demonstrating good performance in removing bias due to unmeasured confounding. We revisited the simulations, finding no evidence of bias reduction.Journal of Statistical Research 2021, Vol. 55, No. 2, pp. 293-297