136 related articles for article (PubMed ID: 27503837)
1. A flexible parametric approach to examining spatial variation in relative survival.
Cramb SM; Mengersen KL; Lambert PC; Ryan LM; Baade PD
Stat Med; 2016 Dec; 35(29):5448-5463. PubMed ID: 27503837
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. A Bayesian piecewise survival cure rate model for spatially clustered data.
Hurtado Rúa SM; Dey DK
Spat Spatiotemporal Epidemiol; 2019 Jun; 29():149-159. PubMed ID: 31128624
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Spatio-temporal relative survival of breast and colorectal cancer in Queensland, Australia 2001-2011.
Cramb SM; Mengersen KL; Baade PD
Spat Spatiotemporal Epidemiol; 2016 Nov; 19():103-114. PubMed ID: 27839574
[TBL] [Abstract][Full Text] [Related]
6. Spatial variation in cancer incidence and survival over time across Queensland, Australia.
Cramb SM; Moraga P; Mengersen KL; Baade PD
Spat Spatiotemporal Epidemiol; 2017 Nov; 23():59-67. PubMed ID: 29108691
[TBL] [Abstract][Full Text] [Related]
7. Spatial smoothing of cancer survival: a Bayesian approach.
Osnes K; Aalen OO
Stat Med; 1999 Aug; 18(16):2087-99. PubMed ID: 10441765
[TBL] [Abstract][Full Text] [Related]
8. A flexible cure rate model for spatially correlated survival data based on generalized extreme value distribution and Gaussian process priors.
Li D; Wang X; Dey DK
Biom J; 2016 Sep; 58(5):1178-97. PubMed ID: 27225466
[TBL] [Abstract][Full Text] [Related]
9. Spatial inequalities in colorectal and breast cancer survival: premature deaths and associated factors.
Cramb SM; Mengersen KL; Turrell G; Baade PD
Health Place; 2012 Nov; 18(6):1412-21. PubMed ID: 22906754
[TBL] [Abstract][Full Text] [Related]
10. Extrapolation of Survival Curves Using Standard Parametric Models and Flexible Parametric Spline Models: Comparisons in Large Registry Cohorts with Advanced Cancer.
Gray J; Sullivan T; Latimer NR; Salter A; Sorich MJ; Ward RL; Karnon J
Med Decis Making; 2021 Feb; 41(2):179-193. PubMed ID: 33349137
[TBL] [Abstract][Full Text] [Related]
11. Spatially Varying Coefficient Inequalities: Evaluating How the Impact of Patient Characteristics on Breast Cancer Survival Varies by Location.
Hsieh JC; Cramb SM; McGree JM; Dunn NA; Baade PD; Mengersen KL
PLoS One; 2016; 11(5):e0155086. PubMed ID: 27149274
[TBL] [Abstract][Full Text] [Related]
12. Objective Bayesian model selection for Cox regression.
Held L; Gravestock I; Sabanés Bové D
Stat Med; 2016 Dec; 35(29):5376-5390. PubMed ID: 27580645
[TBL] [Abstract][Full Text] [Related]
13. Comparing Survival Extrapolation within All-Cause and Relative Survival Frameworks by Standard Parametric Models and Flexible Parametric Spline Models Using the Swedish Cancer Registry.
Chen EY; Leontyeva Y; Lin CN; Wang JD; Clements MS; Dickman PW
Med Decis Making; 2024 Apr; 44(3):269-282. PubMed ID: 38314657
[TBL] [Abstract][Full Text] [Related]
14. Nonparametric survival analysis using Bayesian Additive Regression Trees (BART).
Sparapani RA; Logan BR; McCulloch RE; Laud PW
Stat Med; 2016 Jul; 35(16):2741-53. PubMed ID: 26854022
[TBL] [Abstract][Full Text] [Related]
15. Flexible parametric models for relative survival, with application in coronary heart disease.
Nelson CP; Lambert PC; Squire IB; Jones DR
Stat Med; 2007 Dec; 26(30):5486-98. PubMed ID: 17893893
[TBL] [Abstract][Full Text] [Related]
16. Regression B-spline smoothing in Bayesian disease mapping: with an application to patient safety surveillance.
MacNab YC; Gustafson P
Stat Med; 2007 Oct; 26(24):4455-74. PubMed ID: 17357989
[TBL] [Abstract][Full Text] [Related]
17. Empirical study of the dependence of the results of multivariable flexible survival analyses on model selection strategy.
Binquet C; Abrahamowicz M; Mahboubi A; Jooste V; Faivre J; Bonithon-Kopp C; Quantin C
Stat Med; 2008 Dec; 27(30):6470-88. PubMed ID: 18837067
[TBL] [Abstract][Full Text] [Related]
18. Linear models of coregionalization for multivariate lattice data: a general framework for coregionalized multivariate CAR models.
MacNab YC
Stat Med; 2016 Sep; 35(21):3827-50. PubMed ID: 27091685
[TBL] [Abstract][Full Text] [Related]
19. On identification in Bayesian disease mapping and ecological-spatial regression models.
MacNab YC
Stat Methods Med Res; 2014 Apr; 23(2):134-55. PubMed ID: 22573502
[TBL] [Abstract][Full Text] [Related]
20. Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.
MacNab YC
Stat Methods Med Res; 2016 Aug; 25(4):1118-44. PubMed ID: 27566769
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
