153 related articles for article (PubMed ID: 36315398)
1. Bayesian Method of Borrowing Study-Level Historical Longitudinal Control Data for Mixed-Effects Models with Repeated Measures.
Li H; Jin M; Chung YC; Zhong S; Wang L
Ther Innov Regul Sci; 2023 Jan; 57(1):142-151. PubMed ID: 36315398
[TBL] [Abstract][Full Text] [Related]
2. Bayesian semiparametric meta-analytic-predictive prior for historical control borrowing in clinical trials.
Hupf B; Bunn V; Lin J; Dong C
Stat Med; 2021 Jun; 40(14):3385-3399. PubMed ID: 33851441
[TBL] [Abstract][Full Text] [Related]
3. Bayesian Dynamic Borrowing of Historical Information with Applications to the Analysis of Large-Scale Assessments.
Kaplan D; Chen J; Yavuz S; Lyu W
Psychometrika; 2023 Mar; 88(1):1-30. PubMed ID: 35687222
[TBL] [Abstract][Full Text] [Related]
4. A model-based approach for historical borrowing, with an application to neovascular age-related macular degeneration.
Brizzi F; Steiert B; Pang H; Diack C; Lomax M; Peck R; Morgan Z; Soubret A
Stat Methods Med Res; 2023 Jun; 32(6):1064-1081. PubMed ID: 37082812
[TBL] [Abstract][Full Text] [Related]
5. Addressing statistical issues when leveraging external control data in pediatric clinical trials using Bayesian dynamic borrowing.
Spanakis E; Kron M; Bereswill M; Mukhopadhyay S
J Biopharm Stat; 2023 Nov; 33(6):752-769. PubMed ID: 36507718
[TBL] [Abstract][Full Text] [Related]
6. Simulating and reporting frequentist operating characteristics of clinical trials that borrow external information: Towards a fair comparison in case of one-arm and hybrid control two-arm trials.
Kopp-Schneider A; Wiesenfarth M; Held L; Calderazzo S
Pharm Stat; 2024; 23(1):4-19. PubMed ID: 37632266
[TBL] [Abstract][Full Text] [Related]
7. Covariate-adjusted borrowing of historical control data in randomized clinical trials.
Han B; Zhan J; John Zhong Z; Liu D; Lindborg S
Pharm Stat; 2017 Jul; 16(4):296-308. PubMed ID: 28560815
[TBL] [Abstract][Full Text] [Related]
8. Leveraging historical data into oncology development programs: Two case studies of phase 2 Bayesian augmented control trial designs.
Smith CL; Thomas Z; Enas N; Thorn K; Lahn M; Benhadji K; Cleverly A
Pharm Stat; 2020 May; 19(3):276-290. PubMed ID: 31903699
[TBL] [Abstract][Full Text] [Related]
9. Use of historical control data for assessing treatment effects in clinical trials.
Viele K; Berry S; Neuenschwander B; Amzal B; Chen F; Enas N; Hobbs B; Ibrahim JG; Kinnersley N; Lindborg S; Micallef S; Roychoudhury S; Thompson L
Pharm Stat; 2014; 13(1):41-54. PubMed ID: 23913901
[TBL] [Abstract][Full Text] [Related]
10. A novel power prior approach for borrowing historical control data in clinical trials.
Shi Y; Li W; Liu GF
Stat Methods Med Res; 2023 Mar; 32(3):493-508. PubMed ID: 36601652
[TBL] [Abstract][Full Text] [Related]
11. Comparative Study of Bayesian Information Borrowing Methods in Oncology Clinical Trials.
Su L; Chen X; Zhang J; Yan F
JCO Precis Oncol; 2022 Mar; 6():e2100394. PubMed ID: 35263169
[TBL] [Abstract][Full Text] [Related]
12. BEATS: Bayesian hybrid design with flexible sample size adaptation for time-to-event endpoints.
Bi D; Liu M; Lin J; Liu R
Stat Med; 2023 Dec; 42(30):5708-5722. PubMed ID: 37858287
[TBL] [Abstract][Full Text] [Related]
13. Incorporating historical controls in clinical trials with longitudinal outcomes using the modified power prior.
Qi H; Rizopoulos D; Lesaffre E; van Rosmalen J
Pharm Stat; 2022 Sep; 21(5):818-834. PubMed ID: 35128780
[TBL] [Abstract][Full Text] [Related]
14. Incorporating individual historical controls and aggregate treatment effect estimates into a Bayesian survival trial: a simulation study.
Brard C; Hampson LV; Gaspar N; Le Deley MC; Le Teuff G
BMC Med Res Methodol; 2019 Apr; 19(1):85. PubMed ID: 31018832
[TBL] [Abstract][Full Text] [Related]
15. Critical appraisal of Bayesian dynamic borrowing from an imperfectly commensurate historical control.
Harun N; Liu C; Kim MO
Pharm Stat; 2020 Sep; 19(5):613-625. PubMed ID: 32185886
[TBL] [Abstract][Full Text] [Related]
16. Bayesian borrowing from historical control data in a vaccine efficacy trial.
Peng L; Jin J; Chambonneau L; Zhao X; Zhang J
Pharm Stat; 2023; 22(5):815-835. PubMed ID: 37226586
[TBL] [Abstract][Full Text] [Related]
17. Bayesian adaptive design for covariate-adaptive historical control information borrowing.
Jin H; Kim MO; Scheffler A; Jiang F
Stat Med; 2023 Dec; 42(29):5338-5352. PubMed ID: 37750361
[TBL] [Abstract][Full Text] [Related]
18. An efficient Bayesian platform trial design for borrowing adaptively from historical control data in lymphoma.
Normington J; Zhu J; Mattiello F; Sarkar S; Carlin B
Contemp Clin Trials; 2020 Feb; 89():105890. PubMed ID: 31740427
[TBL] [Abstract][Full Text] [Related]
19. Elastic priors to dynamically borrow information from historical data in clinical trials.
Jiang L; Nie L; Yuan Y
Biometrics; 2023 Mar; 79(1):49-60. PubMed ID: 34437714
[TBL] [Abstract][Full Text] [Related]
20. Bayesian adaptive randomization design incorporating propensity score-matched historical controls.
Sawamoto R; Oba K; Matsuyama Y
Pharm Stat; 2022 Sep; 21(5):1074-1089. PubMed ID: 35278032
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]