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Stat Med. 1995 Nov 15-30;14(21-22):2411-31.

Bayesian estimates of disease maps: how important are priors?

Author information

1
Istituto Scienze Sanitarie Applicate, Universit√° degli Studi di Pavia, Italy.

Abstract

In the fully Bayesian (FB) approach to disease mapping the choice of the hyperprior distribution of the dispersion parameter is a key issue. In this context we investigated the sensitivity of the rate ratio estimates to the choice of the hyperprior via a simulation study. We also compared the performance of the FB approach to mapping disease risk to the conventional approach of mapping maximum likelihood (ML) estimates and p-values. The study was modelled on the incidence data of insulin dependent diabetes mellitus (IDDM) as observed in the communes of Sardinia.

PMID:
8711278
DOI:
10.1002/sim.4780142111
[Indexed for MEDLINE]

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