Assessing treatment effects in observational data with missing confounders: A comparative study of practical doubly-robust and traditional missing data methods

Détails bibliographiques

Publié dans:	arXiv.org (Dec 19, 2024), p. n/a
Auteur principal:	Williamson, Brian D
Autres auteurs:	Krakauer, Chloe, Johnson, Eric, Gruber, Susan, Shepherd, Bryan E, Mark J van der Laan, Lumley, Thomas, Lee, Hana, Hernandez Munoz, Jose J, Zhao, Fengyu, Dutcher, Sarah K, Desai, Rishi, Simon, Gregory E, Shortreed, Susan M, Nelson, Jennifer C, Shaw, Pamela A
Publié:	Cornell University Library, arXiv.org
Sujets:	Comparative studies Data analysis Electronic health records Missing data Data structures Maximum likelihood estimation Error analysis Biomedical data Antidepressants Robustness Synthetic data
Accès en ligne:	Citation/Abstract Full text outside of ProQuest
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