Estimation of the average treatment effect with variable selection and measurement error simultaneously addressed for potential confounders

Autor:	Grace Y. Yi, Li-Pang Chen
Rok vydání:	2023
Předmět:	Statistics and Probability Health Information Management Epidemiology
Zdroj:	Statistical Methods in Medical Research. 32:691-711
ISSN:	1477-0334 0962-2802
DOI:	10.1177/09622802221146308
Popis:	In the framework of causal inference, the inverse probability weighting estimation method and its variants have been commonly employed to estimate the average treatment effect. Such methods, however, are challenged by the presence of irrelevant pre-treatment variables and measurement error. Ignoring these features and naively applying the usual inverse probability weighting estimation procedures may typically yield biased inference results. In this article, we develop an inference method for estimating the average treatment effect with those features taken into account. We establish theoretical properties for the resulting estimator and carry out numerical studies to assess the finite sample performance of the proposed estimator.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7dc43e455a02241e4748eec6218359f7 https://doi.org/10.1177/09622802221146308 Zobrazit plný text záznamu