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 *

134 related articles for article (PubMed ID: 16886733)

  • 1. Modelling geographically referenced survival data with a cure fraction.
    Cooner F; Banerjee S; McBean AM
    Stat Methods Med Res; 2006 Aug; 15(4):307-24. PubMed ID: 16886733
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Semiparametric proportional odds models for spatially correlated survival data.
    Banerjee S; Dey DK
    Lifetime Data Anal; 2005 Jun; 11(2):175-91. PubMed ID: 15938545
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Spatial Data Analysis.
    Banerjee S
    Annu Rev Public Health; 2016; 37():47-60. PubMed ID: 26789381
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prior choice in discrete latent modeling of spatially referenced cancer survival.
    Lawson AB; Choi J; Zhang J
    Stat Methods Med Res; 2014 Apr; 23(2):183-200. PubMed ID: 22556109
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Analysis of cure rate survival data under proportional odds model.
    Gu Y; Sinha D; Banerjee S
    Lifetime Data Anal; 2011 Jan; 17(1):123-34. PubMed ID: 20521166
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Assessment and statistical modeling of the relationship between remotely sensed aerosol optical depth and PM2.5 in the eastern United States.
    Paciorek CJ; Liu Y;
    Res Rep Health Eff Inst; 2012 May; (167):5-83; discussion 85-91. PubMed ID: 22838153
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Parametric models for spatially correlated survival data for individuals with multiple cancers.
    Diva U; Dey DK; Banerjee S
    Stat Med; 2008 May; 27(12):2127-44. PubMed ID: 18167633
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparing multilevel and Bayesian spatial random effects survival models to assess geographical inequalities in colorectal cancer survival: a case study.
    Dasgupta P; Cramb SM; Aitken JF; Turrell G; Baade PD
    Int J Health Geogr; 2014 Oct; 13():36. PubMed ID: 25280499
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Spatial epidemiology: current approaches and future challenges.
    Elliott P; Wartenberg D
    Environ Health Perspect; 2004 Jun; 112(9):998-1006. PubMed ID: 15198920
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Semiparametric Bayesian estimation of quantile function for breast cancer survival data with cured fraction.
    Gupta C; Cobre J; Polpo A; Sinha D
    Biom J; 2016 Sep; 58(5):1164-77. PubMed ID: 27162061
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Spatial modelling of disease using data- and knowledge-driven approaches.
    Stevens KB; Pfeiffer DU
    Spat Spatiotemporal Epidemiol; 2011 Sep; 2(3):125-33. PubMed ID: 22748172
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Modelling spatially correlated survival data for individuals with multiple cancers.
    Diva U; Banerjee S; Dey DK
    Stat Modelling; 2007 Jul; 7(2):191-213. PubMed ID: 19789726
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A transformation class for spatio-temporal survival data with a cure fraction.
    Hurtado Rúa SM; Dey DK
    Stat Methods Med Res; 2016 Feb; 25(1):167-87. PubMed ID: 22514030
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Modelling converging hazards in survival analysis.
    Barker P; Henderson R
    Lifetime Data Anal; 2004 Sep; 10(3):263-81. PubMed ID: 15456107
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A new threshold regression model for survival data with a cure fraction.
    Kim S; Chen MH; Dey DK
    Lifetime Data Anal; 2011 Jan; 17(1):101-22. PubMed ID: 20414804
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Spatially dependent polya tree modeling for survival data.
    Zhao L; Hanson TE
    Biometrics; 2011 Jun; 67(2):391-403. PubMed ID: 20731644
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Estimating and modelling cure in population-based cancer studies within the framework of flexible parametric survival models.
    Andersson TM; Dickman PW; Eloranta S; Lambert PC
    BMC Med Res Methodol; 2011 Jun; 11():96. PubMed ID: 21696598
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Age, period and cohort effects in Bayesian smoothing of spatial cancer survival with geoadditive models.
    Sauleau EA; Hennerfeind A; Buemi A; Held L
    Stat Med; 2007 Jan; 26(1):212-29. PubMed ID: 16526007
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A Case Study Examining the Usefulness of Cure Modelling for the Prediction of Survival Based on Data Maturity.
    Grant TS; Burns D; Kiff C; Lee D
    Pharmacoeconomics; 2020 Apr; 38(4):385-395. PubMed ID: 31848900
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Making the most of spatial information in health: a tutorial in Bayesian disease mapping for areal data.
    Kang SY; Cramb SM; White NM; Ball SJ; Mengersen KL
    Geospat Health; 2016 May; 11(2):428. PubMed ID: 27245803
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.