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Comparing multilevel and Bayesian spatial random effects survival models to assess geographical inequalities in colorectal cancer survival: a case study.

Authors
  • Dasgupta, Paramita
  • Cramb, Susanna M
  • Aitken, Joanne F
  • Turrell, Gavin
  • Baade, Peter D
Type
Published Article
Journal
International journal of health geographics
Publication Date
Jan 01, 2014
Volume
13
Pages
36–36
Identifiers
DOI: 10.1186/1476-072X-13-36
PMID: 25280499
Source
Medline
License
Unknown

Abstract

With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings.

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