BAYESIAN-ANALYSIS OF SPACE-TIME VARIATION IN DISEASE RISK

被引：350

作者：

BERNARDINELLI, L

CLAYTON, D

PASCUTTO, C

MONTOMOLI, C

GHISLANDI, M

SONGINI, M

机构：

[1] INST PUBL HLTH,MRC,BIOSTAT UNIT,CAMBRIDGE CB2 2SR,ENGLAND

[2] OSPED S MICHELE,CTR MALATTIE DISMETAB,I-09134 CAGLIARI,ITALY

来源：

STATISTICS IN MEDICINE | 1995年 / 14卷 / 21-22期

关键词：

D O I：

10.1002/sim.4780142112

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The analysis of variation of risk for a given disease in space and time is a key issue in descriptive epidemiology. When the data are scarce, maximum likelihood estimates of the area-specific risk and of its linear time-trend can be seriously affected by random variation. In this paper, we propose a Bayesian model in which both area-specific intercept and trend are modelled as random effects and correlation between them is allowed for. This model, is an extension of that originally proposed for disease mapping. It is illustrated by the analysis of the cumulative prevalence of insulin dependent diabetes mellitus as observed at the military examination of 18-year-old conscripts born in Sardinia during the period 1936-1971. Data concerning the genetic differentiation of the Sardinian population are used to interpret the results.

引用

页码：2433 / 2443

页数：11

共 19 条

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