137 related articles for article (PubMed ID: 26417963)
1. Nonidentical twins: Comparison of frequentist and Bayesian lasso for Cox models.
Zucknick M; Saadati M; Benner A
Biom J; 2015 Nov; 57(6):959-81. PubMed ID: 26417963
[TBL] [Abstract][Full Text] [Related]
2. High-dimensional Cox models: the choice of penalty as part of the model building process.
Benner A; Zucknick M; Hielscher T; Ittrich C; Mansmann U
Biom J; 2010 Feb; 52(1):50-69. PubMed ID: 20166132
[TBL] [Abstract][Full Text] [Related]
3. L1 penalized estimation in the Cox proportional hazards model.
Goeman JJ
Biom J; 2010 Feb; 52(1):70-84. PubMed ID: 19937997
[TBL] [Abstract][Full Text] [Related]
4. Gradient lasso for Cox proportional hazards model.
Sohn I; Kim J; Jung SH; Park C
Bioinformatics; 2009 Jul; 25(14):1775-81. PubMed ID: 19447787
[TBL] [Abstract][Full Text] [Related]
5. Empirical extensions of the lasso penalty to reduce the false discovery rate in high-dimensional Cox regression models.
Ternès N; Rotolo F; Michiels S
Stat Med; 2016 Jul; 35(15):2561-73. PubMed ID: 26970107
[TBL] [Abstract][Full Text] [Related]
6. Robust estimation of the expected survival probabilities from high-dimensional Cox models with biomarker-by-treatment interactions in randomized clinical trials.
Ternès N; Rotolo F; Michiels S
BMC Med Res Methodol; 2017 May; 17(1):83. PubMed ID: 28532387
[TBL] [Abstract][Full Text] [Related]
7. Applications of Bayesian shrinkage prior models in clinical research with categorical responses.
Bhattacharyya A; Pal S; Mitra R; Rai S
BMC Med Res Methodol; 2022 Apr; 22(1):126. PubMed ID: 35484507
[TBL] [Abstract][Full Text] [Related]
8. Bayesian versus frequentist hypotheses testing in clinical trials with dichotomous and countable outcomes.
Zaslavsky BG
J Biopharm Stat; 2010 Sep; 20(5):985-97. PubMed ID: 20721786
[TBL] [Abstract][Full Text] [Related]
9. An empirical Bayes method for estimating epistatic effects of quantitative trait loci.
Xu S
Biometrics; 2007 Jun; 63(2):513-21. PubMed ID: 17688503
[TBL] [Abstract][Full Text] [Related]
10. Fused lasso algorithm for Cox' proportional hazards and binomial logit models with application to copy number profiles.
Chaturvedi N; de Menezes RX; Goeman JJ
Biom J; 2014 May; 56(3):477-92. PubMed ID: 24496763
[TBL] [Abstract][Full Text] [Related]
11. A permutation approach for selecting the penalty parameter in penalized model selection.
Sabourin JA; Valdar W; Nobel AB
Biometrics; 2015 Dec; 71(4):1185-94. PubMed ID: 26243050
[TBL] [Abstract][Full Text] [Related]
12. Review and evaluation of penalised regression methods for risk prediction in low-dimensional data with few events.
Pavlou M; Ambler G; Seaman S; De Iorio M; Omar RZ
Stat Med; 2016 Mar; 35(7):1159-77. PubMed ID: 26514699
[TBL] [Abstract][Full Text] [Related]
13. Bayesian proportional hazards model with time-varying regression coefficients: a penalized Poisson regression approach.
Lambert P; Eilers PH
Stat Med; 2005 Dec; 24(24):3977-89. PubMed ID: 16320263
[TBL] [Abstract][Full Text] [Related]
14. Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression data.
Gui J; Li H
Bioinformatics; 2005 Jul; 21(13):3001-8. PubMed ID: 15814556
[TBL] [Abstract][Full Text] [Related]
15. The Bayesian adaptive lasso regression.
Alhamzawi R; Ali HTM
Math Biosci; 2018 Sep; 303():75-82. PubMed ID: 29920251
[TBL] [Abstract][Full Text] [Related]
16. The Bayesian Covariance Lasso.
Khondker ZS; Zhu H; Chu H; Lin W; Ibrahim JG
Stat Interface; 2013 Apr; 6(2):243-259. PubMed ID: 24551316
[TBL] [Abstract][Full Text] [Related]
17. A novel non-negative Bayesian stacking modeling method for Cancer survival prediction using high-dimensional omics data.
Shen J; Wang S; Sun H; Huang J; Bai L; Wang X; Dong Y; Tang Z
BMC Med Res Methodol; 2024 May; 24(1):105. PubMed ID: 38702624
[TBL] [Abstract][Full Text] [Related]
18. Bayesian semiparametric analysis of recurrent failure time data using copulas.
Meyer R; Romeo JS
Biom J; 2015 Nov; 57(6):982-1001. PubMed ID: 26153049
[TBL] [Abstract][Full Text] [Related]
19. Bayesian two-step Lasso strategy for biomarker selection in personalized medicine development for time-to-event endpoints.
Gu X; Yin G; Lee JJ
Contemp Clin Trials; 2013 Nov; 36(2):642-50. PubMed ID: 24075829
[TBL] [Abstract][Full Text] [Related]
20. Bayesian random-effects threshold regression with application to survival data with nonproportional hazards.
Pennell ML; Whitmore GA; Ting Lee ML
Biostatistics; 2010 Jan; 11(1):111-26. PubMed ID: 19828558
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
