151 related articles for article (PubMed ID: 34726285)
1. Multiple imputation procedures for estimating causal effects with multiple treatments with application to the comparison of healthcare providers.
Silva GC; Gutman R
Stat Med; 2022 Jan; 41(1):208-226. PubMed ID: 34726285
[TBL] [Abstract][Full Text] [Related]
2. Estimation of causal effects of multiple treatments in observational studies with a binary outcome.
Hu L; Gu C; Lopez M; Ji J; Wisnivesky J
Stat Methods Med Res; 2020 Nov; 29(11):3218-3234. PubMed ID: 32450775
[TBL] [Abstract][Full Text] [Related]
3. Approximate Bayesian Bootstrap procedures to estimate multilevel treatment effects in observational studies with application to type 2 diabetes treatment regimens.
Scotina AD; Zullo AR; Smith RJ; Gutman R
Stat Methods Med Res; 2020 Nov; 29(11):3362-3380. PubMed ID: 32588747
[TBL] [Abstract][Full Text] [Related]
4. A Bayesian nonparametric approach to causal inference on quantiles.
Xu D; Daniels MJ; Winterstein AG
Biometrics; 2018 Sep; 74(3):986-996. PubMed ID: 29478267
[TBL] [Abstract][Full Text] [Related]
5. Bayesian causal inference for observational studies with missingness in covariates and outcomes.
Zang H; Kim HJ; Huang B; Szczesniak R
Biometrics; 2023 Dec; 79(4):3624-3636. PubMed ID: 37553770
[TBL] [Abstract][Full Text] [Related]
6. Reformulating provider profiling by grouping providers treating similar patients prior to evaluating performance.
Silva GC; Gutman R
Biostatistics; 2023 Oct; 24(4):962-984. PubMed ID: 35661195
[TBL] [Abstract][Full Text] [Related]
7. Matching algorithms for causal inference with multiple treatments.
Scotina AD; Gutman R
Stat Med; 2019 Jul; 38(17):3139-3167. PubMed ID: 31066079
[TBL] [Abstract][Full Text] [Related]
8. Propensity score matching after multiple imputation when a confounder has missing data.
Ségalas C; Leyrat C; Carpenter JR; Williamson E
Stat Med; 2023 Mar; 42(7):1082-1095. PubMed ID: 36695043
[TBL] [Abstract][Full Text] [Related]
9. Estimating heterogeneous survival treatment effect in observational data using machine learning.
Hu L; Ji J; Li F
Stat Med; 2021 Sep; 40(21):4691-4713. PubMed ID: 34114252
[TBL] [Abstract][Full Text] [Related]
10. Bayesian nonparametric generative models for causal inference with missing at random covariates.
Roy J; Lum KJ; Zeldow B; Dworkin JD; Re VL; Daniels MJ
Biometrics; 2018 Dec; 74(4):1193-1202. PubMed ID: 29579341
[TBL] [Abstract][Full Text] [Related]
11. Generalized propensity score approach to causal inference with spatial interference.
Giffin A; Reich BJ; Yang S; Rappold AG
Biometrics; 2023 Sep; 79(3):2220-2231. PubMed ID: 35996756
[TBL] [Abstract][Full Text] [Related]
12. Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases.
Wendling T; Jung K; Callahan A; Schuler A; Shah NH; Gallego B
Stat Med; 2018 Oct; 37(23):3309-3324. PubMed ID: 29862536
[TBL] [Abstract][Full Text] [Related]
13. Sequential BART for imputation of missing covariates.
Xu D; Daniels MJ; Winterstein AG
Biostatistics; 2016 Jul; 17(3):589-602. PubMed ID: 26980459
[TBL] [Abstract][Full Text] [Related]
14. Bayesian nonparametric adjustment of confounding.
Kim C; Tec M; Zigler C
Biometrics; 2023 Dec; 79(4):3252-3265. PubMed ID: 36718599
[TBL] [Abstract][Full Text] [Related]
15. Propensity score analysis with partially observed covariates: How should multiple imputation be used?
Leyrat C; Seaman SR; White IR; Douglas I; Smeeth L; Kim J; Resche-Rigon M; Carpenter JR; Williamson EJ
Stat Methods Med Res; 2019 Jan; 28(1):3-19. PubMed ID: 28573919
[TBL] [Abstract][Full Text] [Related]
16. Simulation-based estimators of analytically intractable causal effects.
Linero AR
Biometrics; 2022 Sep; 78(3):1001-1017. PubMed ID: 34051105
[TBL] [Abstract][Full Text] [Related]
17. Estimation of causal effects of binary treatments in unconfounded studies.
Gutman R; Rubin DB
Stat Med; 2015 Nov; 34(26):3381-98. PubMed ID: 26013308
[TBL] [Abstract][Full Text] [Related]
18. ESTIMATING POPULATION AVERAGE CAUSAL EFFECTS IN THE PRESENCE OF NON-OVERLAP: THE EFFECT OF NATURAL GAS COMPRESSOR STATION EXPOSURE ON CANCER MORTALITY.
Nethery RC; Mealli F; Dominici F
Ann Appl Stat; 2019 Jun; 13(2):1242-1267. PubMed ID: 31346355
[TBL] [Abstract][Full Text] [Related]
19. Comparison of methods for handling covariate missingness in propensity score estimation with a binary exposure.
Coffman DL; Zhou J; Cai X
BMC Med Res Methodol; 2020 Jun; 20(1):168. PubMed ID: 32586271
[TBL] [Abstract][Full Text] [Related]
20. A flexible approach for variable selection in large-scale healthcare database studies with missing covariate and outcome data.
Lin JJ; Hu L; Huang C; Jiayi J; Lawrence S; Govindarajulu U
BMC Med Res Methodol; 2022 May; 22(1):132. PubMed ID: 35508974
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
