378 related articles for article (PubMed ID: 25087884)
1. The use of bootstrapping when using propensity-score matching without replacement: a simulation study.
Austin PC; Small DS
Stat Med; 2014 Oct; 33(24):4306-19. PubMed ID: 25087884
[TBL] [Abstract][Full Text] [Related]
2. Type I error rates, coverage of confidence intervals, and variance estimation in propensity-score matched analyses.
Austin PC
Int J Biostat; 2009 Apr; 5(1):Article 13. PubMed ID: 20949126
[TBL] [Abstract][Full Text] [Related]
3. Evaluating the use of bootstrapping in cohort studies conducted with 1:1 propensity score matching-A plasmode simulation study.
Desai RJ; Wyss R; Abdia Y; Toh S; Johnson M; Lee H; Karami S; Major JM; Nguyen M; Wang SV; Franklin JM; Gagne JJ
Pharmacoepidemiol Drug Saf; 2019 Jun; 28(6):879-886. PubMed ID: 31020732
[TBL] [Abstract][Full Text] [Related]
4. Comparing paired vs non-paired statistical methods of analyses when making inferences about absolute risk reductions in propensity-score matched samples.
Austin PC
Stat Med; 2011 May; 30(11):1292-301. PubMed ID: 21337595
[TBL] [Abstract][Full Text] [Related]
5. Bootstrap vs asymptotic variance estimation when using propensity score weighting with continuous and binary outcomes.
Austin PC
Stat Med; 2022 Sep; 41(22):4426-4443. PubMed ID: 35841200
[TBL] [Abstract][Full Text] [Related]
6. The performance of different propensity score methods for estimating marginal hazard ratios.
Austin PC
Stat Med; 2013 Jul; 32(16):2837-49. PubMed ID: 23239115
[TBL] [Abstract][Full Text] [Related]
7. Variance estimation of the risk difference when using propensity-score matching and weighting with time-to-event outcomes.
Cafri G; Austin PC
Pharm Stat; 2023; 22(5):880-902. PubMed ID: 37258420
[TBL] [Abstract][Full Text] [Related]
8. The performance of different propensity-score methods for estimating differences in proportions (risk differences or absolute risk reductions) in observational studies.
Austin PC
Stat Med; 2010 Sep; 29(20):2137-48. PubMed ID: 20108233
[TBL] [Abstract][Full Text] [Related]
9. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies.
Austin PC
Pharm Stat; 2011; 10(2):150-61. PubMed ID: 20925139
[TBL] [Abstract][Full Text] [Related]
10. Double propensity-score adjustment: A solution to design bias or bias due to incomplete matching.
Austin PC
Stat Methods Med Res; 2017 Feb; 26(1):201-222. PubMed ID: 25038071
[TBL] [Abstract][Full Text] [Related]
11. Propensity score matching and complex surveys.
Austin PC; Jembere N; Chiu M
Stat Methods Med Res; 2018 Apr; 27(4):1240-1257. PubMed ID: 27460539
[TBL] [Abstract][Full Text] [Related]
12. Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis.
Austin PC
Stat Med; 2016 Dec; 35(30):5642-5655. PubMed ID: 27549016
[TBL] [Abstract][Full Text] [Related]
13. The performance of different propensity score methods for estimating absolute effects of treatments on survival outcomes: A simulation study.
Austin PC; Schuster T
Stat Methods Med Res; 2016 Oct; 25(5):2214-2237. PubMed ID: 24463885
[TBL] [Abstract][Full Text] [Related]
14. Some methods of propensity-score matching had superior performance to others: results of an empirical investigation and Monte Carlo simulations.
Austin PC
Biom J; 2009 Feb; 51(1):171-84. PubMed ID: 19197955
[TBL] [Abstract][Full Text] [Related]
15. Variance estimation when using propensity-score matching with replacement with survival or time-to-event outcomes.
Austin PC; Cafri G
Stat Med; 2020 May; 39(11):1623-1640. PubMed ID: 32109319
[TBL] [Abstract][Full Text] [Related]
16. A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study.
Austin PC; Grootendorst P; Anderson GM
Stat Med; 2007 Feb; 26(4):734-53. PubMed ID: 16708349
[TBL] [Abstract][Full Text] [Related]
17. Propensity score interval matching: using bootstrap confidence intervals for accommodating estimation errors of propensity scores.
Pan W; Bai H
BMC Med Res Methodol; 2015 Jul; 15():53. PubMed ID: 26215035
[TBL] [Abstract][Full Text] [Related]
18. Estimating the effect of treatment on binary outcomes using full matching on the propensity score.
Austin PC; Stuart EA
Stat Methods Med Res; 2017 Dec; 26(6):2505-2525. PubMed ID: 26329750
[TBL] [Abstract][Full Text] [Related]
19. Oversampling and replacement strategies in propensity score matching: a critical review focused on small sample size in clinical settings.
Bottigliengo D; Baldi I; Lanera C; Lorenzoni G; Bejko J; Bottio T; Tarzia V; Carrozzini M; Gerosa G; Berchialla P; Gregori D
BMC Med Res Methodol; 2021 Nov; 21(1):256. PubMed ID: 34809559
[TBL] [Abstract][Full Text] [Related]
20.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Next] [New Search]
