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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

109 related articles for article (PubMed ID: 2049501)

  • 1. A nonproportional hazards Weibull accelerated failure time regression model.
    Anderson KM
    Biometrics; 1991 Mar; 47(1):281-8. PubMed ID: 2049501
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Maximum likelihood estimation for interval-censored data using a Weibull-based accelerated failure time model.
    Odell PM; Anderson KM; D'Agostino RB
    Biometrics; 1992 Sep; 48(3):951-9. PubMed ID: 1420849
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Twenty-five-year cardiovascular disease incidence among middle-aged men. Disease burden, time shape, predictors, risk probabilities.
    Menotti A; Lanti M; Puddu PE
    Ital Heart J; 2000 Nov; 1(11):749-57. PubMed ID: 11110517
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Modeling multivariate discrete failure time data.
    Shih JH
    Biometrics; 1998 Sep; 54(3):1115-28. PubMed ID: 9750256
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Piecewise exponential survival trees with time-dependent covariates.
    Huang X; Chen S; Soong SJ
    Biometrics; 1998 Dec; 54(4):1420-33. PubMed ID: 9883542
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Regression analysis of interval-censored survival data with covariates using log-linear models.
    Kim DK
    Biometrics; 1997 Dec; 53(4):1274-83. PubMed ID: 9423249
    [TBL] [Abstract][Full Text] [Related]  

  • 7. History of acute coronary events during the predialysis phase of chronic kidney disease is a strong risk factor for major adverse cardiac events in patients initiating haemodialysis.
    Tanaka Y; Joki N; Hase H
    Nephrol Dial Transplant; 2007 Oct; 22(10):2917-23. PubMed ID: 17644817
    [TBL] [Abstract][Full Text] [Related]  

  • 8. SAS macros for estimation of the cumulative incidence functions based on a Cox regression model for competing risks survival data.
    Rosthøj S; Andersen PK; Abildstrom SZ
    Comput Methods Programs Biomed; 2004 Apr; 74(1):69-75. PubMed ID: 14992828
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Inference for the proportional hazards model with misclassified discrete-valued covariates.
    Zucker DM; Spiegelman D
    Biometrics; 2004 Jun; 60(2):324-34. PubMed ID: 15180657
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Reduced-rank hazard regression for modelling non-proportional hazards.
    Perperoglou A; le Cessie S; van Houwelingen HC
    Stat Med; 2006 Aug; 25(16):2831-45. PubMed ID: 16158396
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A regression survival model for testing the proportional hazards hypothesis.
    Quantin C; Moreau T; Asselain B; Maccario J; Lellouch J
    Biometrics; 1996 Sep; 52(3):874-85. PubMed ID: 8924576
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Estimating equations with incomplete categorical covariates in the Cox model.
    Lipsitz SR; Ibrahim JG
    Biometrics; 1998 Sep; 54(3):1002-13. PubMed ID: 9750248
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparison of the Framingham risk function-based coronary chart with risk function from an Italian population study.
    Menotti A; Puddu PE; Lanti M
    Eur Heart J; 2000 Mar; 21(5):365-70. PubMed ID: 10666350
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Partly conditional survival models for longitudinal data.
    Zheng Y; Heagerty PJ
    Biometrics; 2005 Jun; 61(2):379-91. PubMed ID: 16011684
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A joint model for survival and longitudinal data measured with error.
    Wulfsohn MS; Tsiatis AA
    Biometrics; 1997 Mar; 53(1):330-9. PubMed ID: 9147598
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Prediction of early and delayed postoperative deaths after coronary artery bypass surgery alone in Italy. Multivariate predictions based on Cox and logistic models and a chart based on the accelerated failure time model.
    Puddu PE; Brancaccio G; Leacche M; Monti F; Lanti M; Menotti A; Gaudio C; Papalia U; Marino B;
    Ital Heart J; 2002 Mar; 3(3):166-81. PubMed ID: 11974661
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Heterogeneity models of disease susceptibility, with application to diabetic nephropathy.
    Hougaard P; Myglegaard P; Borch-Johnsen K
    Biometrics; 1994 Dec; 50(4):1178-88. PubMed ID: 7787000
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Fitting semiparametric additive hazards models using standard statistical software.
    Schaubel DE; Wei G
    Biom J; 2007 Aug; 49(5):719-30. PubMed ID: 17638295
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Depressive symptoms, coronary heart disease, and overall mortality in the Framingham Heart Study.
    Wulsin LR; Evans JC; Vasan RS; Murabito JM; Kelly-Hayes M; Benjamin EJ
    Psychosom Med; 2005; 67(5):697-702. PubMed ID: 16204426
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Modelling survival in acute severe illness: Cox versus accelerated failure time models.
    Moran JL; Bersten AD; Solomon PJ; Edibam C; Hunt T;
    J Eval Clin Pract; 2008 Feb; 14(1):83-93. PubMed ID: 18211649
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.