360 related articles for article (PubMed ID: 28742252)
21. 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]
22. Machine learning outcome regression improves doubly robust estimation of average causal effects.
Choi BY; Wang CP; Gelfond J
Pharmacoepidemiol Drug Saf; 2020 Sep; 29(9):1120-1133. PubMed ID: 32716126
[TBL] [Abstract][Full Text] [Related]
23. 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]
24. Doubly-robust methods for differences in restricted mean lifetimes using pseudo-observations.
Choi S; Choi T; Lee HY; Han SW; Bandyopadhyay D
Pharm Stat; 2022 Nov; 21(6):1185-1198. PubMed ID: 35524651
[TBL] [Abstract][Full Text] [Related]
25. Augmented Inverse Probability Weighting and the Double Robustness Property.
Kurz CF
Med Decis Making; 2022 Feb; 42(2):156-167. PubMed ID: 34225519
[TBL] [Abstract][Full Text] [Related]
26. Weighted estimation of the accelerated failure time model in the presence of dependent censoring.
Cho Y; Ghosh D
PLoS One; 2015; 10(4):e0124381. PubMed ID: 25909753
[TBL] [Abstract][Full Text] [Related]
27. Machine Learning for Causal Inference: On the Use of Cross-fit Estimators.
Zivich PN; Breskin A
Epidemiology; 2021 May; 32(3):393-401. PubMed ID: 33591058
[TBL] [Abstract][Full Text] [Related]
28. Two-stage estimation to adjust for treatment switching in randomised trials: a simulation study investigating the use of inverse probability weighting instead of re-censoring.
Latimer NR; Abrams KR; Siebert U
BMC Med Res Methodol; 2019 Mar; 19(1):69. PubMed ID: 30935369
[TBL] [Abstract][Full Text] [Related]
29. A quantile regression model for failure-time data with time-dependent covariates.
Gorfine M; Goldberg Y; Ritov Y
Biostatistics; 2017 Jan; 18(1):132-146. PubMed ID: 27485534
[TBL] [Abstract][Full Text] [Related]
30. Estimating population treatment effects from a survey subsample.
Rudolph KE; Díaz I; Rosenblum M; Stuart EA
Am J Epidemiol; 2014 Oct; 180(7):737-48. PubMed ID: 25190679
[TBL] [Abstract][Full Text] [Related]
31. Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals.
Almirall D; Griffin BA; McCaffrey DF; Ramchand R; Yuen RA; Murphy SA
Stat Med; 2014 Sep; 33(20):3466-87. PubMed ID: 23873437
[TBL] [Abstract][Full Text] [Related]
32. Subclassification estimation of the weighted average treatment effect.
Choi BY
Biom J; 2021 Dec; 63(8):1706-1728. PubMed ID: 34270815
[TBL] [Abstract][Full Text] [Related]
33. The inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic: an unbiased estimator in the presence of independent censoring.
Dong G; Mao L; Huang B; Gamalo-Siebers M; Wang J; Yu G; Hoaglin DC
J Biopharm Stat; 2020 Sep; 30(5):882-899. PubMed ID: 32552451
[TBL] [Abstract][Full Text] [Related]
34. Double inverse-weighted estimation of cumulative treatment effects under nonproportional hazards and dependent censoring.
Schaubel DE; Wei G
Biometrics; 2011 Mar; 67(1):29-38. PubMed ID: 20560935
[TBL] [Abstract][Full Text] [Related]
35. 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]
36. Mediation Analysis for Censored Survival Data Under an Accelerated Failure Time Model.
Fulcher IR; Tchetgen Tchetgen EJ; Williams PL
Epidemiology; 2017 Sep; 28(5):660-666. PubMed ID: 28574921
[TBL] [Abstract][Full Text] [Related]
37. 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]
38. Analysis of accelerated failure time data with dependent censoring using auxiliary variables via nonparametric multiple imputation.
Hsu CH; Taylor JM; Hu C
Stat Med; 2015 Aug; 34(19):2768-80. PubMed ID: 25999295
[TBL] [Abstract][Full Text] [Related]
39. Targeted maximum likelihood based causal inference: Part I.
van der Laan MJ
Int J Biostat; 2010; 6(2):Article 2. PubMed ID: 21969992
[TBL] [Abstract][Full Text] [Related]
40. Adjustment for Baseline Covariates to Increase Efficiency in RCTs with Binary Endpoint: A Comparison of Bayesian and Frequentist Approaches.
Berchialla P; Sciannameo V; Urru S; Lanera C; Azzolina D; Gregori D; Baldi I
Int J Environ Res Public Health; 2021 Jul; 18(15):. PubMed ID: 34360051
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
