These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
156 related articles for article (PubMed ID: 35419255)
1. Evaluation of Surrogate Endpoints Using Information-Theoretic Measure of Association Based on Havrda and Charvat Entropy. Del Carmen Pardo M; Zhao Q; Jin H; Lu Y Mathematics (Basel); 2022 Feb; 10(3):. PubMed ID: 35419255 [TBL] [Abstract][Full Text] [Related]
2. A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. Brochet T; Lapuyade-Lahorgue J; Huat A; Thureau S; Pasquier D; Gardin I; Modzelewski R; Gibon D; Thariat J; Grégoire V; Vera P; Ruan S Entropy (Basel); 2022 Mar; 24(4):. PubMed ID: 35455101 [TBL] [Abstract][Full Text] [Related]
3. Point set registration using Havrda-Charvat-Tsallis entropy measures. Tustison NJ; Awate SP; Song G; Cook TS; Gee JC IEEE Trans Med Imaging; 2011 Feb; 30(2):451-60. PubMed ID: 20937578 [TBL] [Abstract][Full Text] [Related]
4. Information-theory based surrogate marker evaluation from several randomized clinical trials with continuous true and binary surrogate endpoints. Pryseley A; Tilahun A; Alonso A; Molenberghs G Clin Trials; 2007; 4(6):587-97. PubMed ID: 18042568 [TBL] [Abstract][Full Text] [Related]
5. An information-theoretic approach for the assessment of a continuous outcome as a surrogate for a binary true endpoint based on causal inference: Application to vaccine evaluation. Alonso Abad A; Ong F; Stijven F; Van der Elst W; Molenberghs G; Van Keilegom I; Verbeke G; Callegaro A Stat Med; 2024 Mar; 43(6):1083-1102. PubMed ID: 38164018 [TBL] [Abstract][Full Text] [Related]
6. A maximum entropy approach for the evaluation of surrogate endpoints based on causal inference. Alonso A; Van der Elst W; Molenberghs G Stat Med; 2018 Dec; 37(29):4525-4538. PubMed ID: 30141219 [TBL] [Abstract][Full Text] [Related]
7. Evaluating time to cancer recurrence as a surrogate marker for survival from an information theory perspective. Alonso A; Molenberghs G Stat Methods Med Res; 2008 Oct; 17(5):497-504. PubMed ID: 18285443 [TBL] [Abstract][Full Text] [Related]
8. Surrogate marker evaluation from an information theory perspective. Alonso A; Molenberghs G Biometrics; 2007 Mar; 63(1):180-6. PubMed ID: 17447943 [TBL] [Abstract][Full Text] [Related]
9. Validation of surrogate markers in multiple randomized clinical trials with repeated measurements: canonical correlation approach. Alonso A; Geys H; Molenberghs G; Kenward MG; Vangeneugden T Biometrics; 2004 Dec; 60(4):845-53. PubMed ID: 15606404 [TBL] [Abstract][Full Text] [Related]
10. Information theory-based surrogate marker evaluation from several randomized clinical trials with binary endpoints, using SAS. Tilahun A; Pryseley A; Alonso A; Molenberghs G J Biopharm Stat; 2008; 18(2):326-41. PubMed ID: 18327724 [TBL] [Abstract][Full Text] [Related]
11. Alternative methods to evaluate trial level surrogacy. Abrahantes JC; Shkedy Z; Molenberghs G Clin Trials; 2008; 5(3):194-208. PubMed ID: 18559408 [TBL] [Abstract][Full Text] [Related]
12. A novel automatic suspicious mass regions identification using Havrda & Charvat entropy and Otsu's N thresholding. Kurt B; Nabiyev VV; Turhan K Comput Methods Programs Biomed; 2014 May; 114(3):349-60. PubMed ID: 24681199 [TBL] [Abstract][Full Text] [Related]
13. A unifying approach for surrogate marker validation based on Prentice's criteria. Alonso A; Molenberghs G; Geys H; Buyse M; Vangeneugden T Stat Med; 2006 Jan; 25(2):205-21. PubMed ID: 16220497 [TBL] [Abstract][Full Text] [Related]
14. A reflection on the causal interpretation of individual-level surrogacy. Alonso A; Van Der Elst W; Molenberghs G; Florez AJ J Biopharm Stat; 2019; 29(3):529-540. PubMed ID: 30773114 [TBL] [Abstract][Full Text] [Related]
15. Correction: Brochet et al. A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. Brochet T; Lapuyade-Lahorgue J; Huat A; Thureau S; Pasquier D; Gardin I; Modzelewski R; Gibon D; Thariat J; Grégoire V; Vera P; Ruan S Entropy (Basel); 2022 May; 24(5):. PubMed ID: 35626628 [TBL] [Abstract][Full Text] [Related]
17. Statistical challenges in the evaluation of surrogate endpoints in randomized trials. Molenberghs G; Buyse M; Geys H; Renard D; Burzykowski T; Alonso A Control Clin Trials; 2002 Dec; 23(6):607-25. PubMed ID: 12505240 [TBL] [Abstract][Full Text] [Related]
18. Is blood pressure reduction a valid surrogate endpoint for stroke prevention? An analysis incorporating a systematic review of randomised controlled trials, a by-trial weighted errors-in-variables regression, the surrogate threshold effect (STE) and the Biomarker-Surrogacy (BioSurrogate) Evaluation Schema (BSES). Lassere MN; Johnson KR; Schiff M; Rees D BMC Med Res Methodol; 2012 Mar; 12():27. PubMed ID: 22409774 [TBL] [Abstract][Full Text] [Related]
19. An information-theoretic approach for the evaluation of surrogate endpoints based on causal inference. Alonso A; Van der Elst W; Molenberghs G; Buyse M; Burzykowski T Biometrics; 2016 Sep; 72(3):669-77. PubMed ID: 26864244 [TBL] [Abstract][Full Text] [Related]
20. Proportion of treatment effect mediated by surrogate endpoints. Kuroki M; Shingaki R; Qu Y Biom J; 2021 Jan; 63(1):105-121. PubMed ID: 33200481 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]