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Inference on a collapsed margin in disease mapping
Author(s) -
Byers Simon,
Besag Julian
Publication year - 2000
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/1097-0258(20000915/30)19:17/18<2243::aid-sim566>3.0.co;2-k
Subject(s) - covariate , margin (machine learning) , inference , econometrics , computer science , population , prostate cancer , statistics , data set , set (abstract data type) , demography , geography , cancer , artificial intelligence , medicine , machine learning , mathematics , sociology , programming language
This paper describes a method for estimating the risk from a disease over a set of contiguous geographical regions, when data on a potentially important covariate, such as race, are not available. Conditions under which the extra margin can be recovered are suggested. An application to prostate cancer mortality among the non‐white population in the counties of the U.S.A. is discussed. Copyright © 2000 John Wiley & Sons, Ltd.