BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

140 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 RĂșa 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.