FJRubio67/LBANS/
; Radice, R and Rubio, FJ
(2022).
FJRubio67/LBANS/.
[Dataset].
Github.
https://github.com/FJRubio67/LBANS/
Two data examples of link-based additive net survival models based on the paper. The models are fitted using the R package GJRM. The first example analyses the Simulacrum dataset (https://simulacrum.healthdatainsight.org.uk/) and focuses on differences in lung cancer survival according to different deprivation categories. The second example analyses the LeukSurv dataset from the R package spBayesSurv and provides additional insight on how to model spatial components. Note, however, that we do not have access to life tables from those times based on the Townsend score so for the purpose of the example we used generic values of the population hazards based on more recent life tables.
Alternative Title
A unifying framework for flexible excess hazard modelling with applications in cancer epidemiology
Keywords
Cancer epidemiology; Cancer survival; Additive predictor; Excess hazard| Item Type | Dataset |
|---|---|
| Resource Type |
Resource Type Resource Description Software R script |
| Capture method | Other |
| Date | 4 May 2022 |
| Language(s) of written materials | English |
| Creator(s) |
Eletti, A; Marra, G; Quaresma, M; Radice, R and Rubio, FJ
|
| LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology |
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
| Funders |
Project Funder Grant Number Funder URI Cancer Research UK Population Research Committee C7923/A29018 http://dx.doi.org/10.13039/501100000289 |
| Date Deposited | 28 Jun 2022 15:47 |
| Last Modified | 28 Jun 2022 15:47 |
| Publisher | Github |
No files available. Please consult associated links.
