281 related articles for article (PubMed ID: 35839293)
21. AIPW: An R Package for Augmented Inverse Probability-Weighted Estimation of Average Causal Effects.
Zhong Y; Kennedy EH; Bodnar LM; Naimi AI
Am J Epidemiol; 2021 Dec; 190(12):2690-2699. PubMed ID: 34268567
[TBL] [Abstract][Full Text] [Related]
22. Collaborative double robust targeted maximum likelihood estimation.
van der Laan MJ; Gruber S
Int J Biostat; 2010 May; 6(1):Article 17. PubMed ID: 20628637
[TBL] [Abstract][Full Text] [Related]
23. Data-Adaptive Bias-Reduced Doubly Robust Estimation.
Vermeulen K; Vansteelandt S
Int J Biostat; 2016 May; 12(1):253-82. PubMed ID: 27227724
[TBL] [Abstract][Full Text] [Related]
24. Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial.
Smith MJ; Mansournia MA; Maringe C; Zivich PN; Cole SR; Leyrat C; Belot A; Rachet B; Luque-Fernandez MA
Stat Med; 2022 Jan; 41(2):407-432. PubMed ID: 34713468
[TBL] [Abstract][Full Text] [Related]
25. Data-Adaptive Selection of the Propensity Score Truncation Level for Inverse-Probability-Weighted and Targeted Maximum Likelihood Estimators of Marginal Point Treatment Effects.
Gruber S; Phillips RV; Lee H; van der Laan MJ
Am J Epidemiol; 2022 Aug; 191(9):1640-1651. PubMed ID: 35512316
[TBL] [Abstract][Full Text] [Related]
26. Inverse probability of treatment weighting with generalized linear outcome models for doubly robust estimation.
Gabriel EE; Sachs MC; Martinussen T; Waernbaum I; Goetghebeur E; Vansteelandt S; Sjölander A
Stat Med; 2024 Feb; 43(3):534-547. PubMed ID: 38096856
[TBL] [Abstract][Full Text] [Related]
27. Robust inference on the average treatment effect using the outcome highly adaptive lasso.
Ju C; Benkeser D; van der Laan MJ
Biometrics; 2020 Mar; 76(1):109-118. PubMed ID: 31350906
[TBL] [Abstract][Full Text] [Related]
28. Doubly robust nonparametric inference on the average treatment effect.
Benkeser D; Carone M; Laan MJV; Gilbert PB
Biometrika; 2017 Dec; 104(4):863-880. PubMed ID: 29430041
[TBL] [Abstract][Full Text] [Related]
29. Comparing Parametric, Nonparametric, and Semiparametric Estimators: The Weibull Trials.
Cole SR; Edwards JK; Breskin A; Hudgens MG
Am J Epidemiol; 2021 Aug; 190(8):1643-1651. PubMed ID: 33569578
[TBL] [Abstract][Full Text] [Related]
30. Effect Estimation in Point-Exposure Studies with Binary Outcomes and High-Dimensional Covariate Data - A Comparison of Targeted Maximum Likelihood Estimation and Inverse Probability of Treatment Weighting.
Pang M; Schuster T; Filion KB; Schnitzer ME; Eberg M; Platt RW
Int J Biostat; 2016 Nov; 12(2):. PubMed ID: 27889705
[TBL] [Abstract][Full Text] [Related]
31. Impact of outcome model misspecification on regression and doubly-robust inverse probability weighting to estimate causal effect.
Lefebvre G; Gustafson P
Int J Biostat; 2010; 6(2):Article 15. PubMed ID: 21969999
[TBL] [Abstract][Full Text] [Related]
32. Covariate selection with group lasso and doubly robust estimation of causal effects.
Koch B; Vock DM; Wolfson J
Biometrics; 2018 Mar; 74(1):8-17. PubMed ID: 28636276
[TBL] [Abstract][Full Text] [Related]
33. Doubly robust nonparametric instrumental variable estimators for survival outcomes.
Lee Y; Kennedy EH; Mitra N
Biostatistics; 2023 Apr; 24(2):518-537. PubMed ID: 34676400
[TBL] [Abstract][Full Text] [Related]
34. Evaluating the robustness of targeted maximum likelihood estimators via realistic simulations in nutrition intervention trials.
Li H; Rosete S; Coyle J; Phillips RV; Hejazi NS; Malenica I; Arnold BF; Benjamin-Chung J; Mertens A; Colford JM; van der Laan MJ; Hubbard AE
Stat Med; 2022 May; 41(12):2132-2165. PubMed ID: 35172378
[TBL] [Abstract][Full Text] [Related]
35. Statistical inference for data-adaptive doubly robust estimators with survival outcomes.
Díaz I
Stat Med; 2019 Jul; 38(15):2735-2748. PubMed ID: 30950107
[TBL] [Abstract][Full Text] [Related]
36. Evaluating Flexible Modeling of Continuous Covariates in Inverse-Weighted Estimators.
Kyle RP; Moodie EEM; Klein MB; Abrahamowicz M
Am J Epidemiol; 2019 Jun; 188(6):1181-1191. PubMed ID: 30649165
[TBL] [Abstract][Full Text] [Related]
37. Variable selection for causal mediation analysis using LASSO-based methods.
Ye Z; Zhu Y; Coffman DL
Stat Methods Med Res; 2021 Jun; 30(6):1413-1427. PubMed ID: 33755518
[TBL] [Abstract][Full Text] [Related]
38. Doubly robust estimators of causal exposure effects with missing data in the outcome, exposure or a confounder.
Williamson EJ; Forbes A; Wolfe R
Stat Med; 2012 Dec; 31(30):4382-400. PubMed ID: 23086504
[TBL] [Abstract][Full Text] [Related]
39. Understanding and diagnosing the potential for bias when using machine learning methods with doubly robust causal estimators.
Bahamyirou A; Blais L; Forget A; Schnitzer ME
Stat Methods Med Res; 2019 Jun; 28(6):1637-1650. PubMed ID: 29717941
[TBL] [Abstract][Full Text] [Related]
40. Statistical methods for incomplete data: Some results on model misspecification.
McIsaac M; Cook RJ
Stat Methods Med Res; 2017 Feb; 26(1):248-267. PubMed ID: 25063681
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
