Bayesian analysis of the differences of count data.

Abstract:

:Paired count data usually arise in medicine when before and after treatment measurements are considered. In the present paper we assume that the correlated paired count data follow a bivariate Poisson distribution in order to derive the distribution of their difference. The derived distribution is shown to be the same as the one derived for the difference of the independent Poisson variables, thus recasting interest on the distribution introduced by Skellam. Using this distribution we remove correlation, which naturally exists in paired data, and we improve the quality of our inference by using exact distributions instead of normal approximations. The zero-inflated version is considered to account for an excess of zero counts. Bayesian estimation and hypothesis testing for the models considered are discussed. An example from dental epidemiology is used to illustrate the proposed methodology.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Karlis D,Ntzoufras I

doi

10.1002/sim.2382

subject

Has Abstract

pub_date

2006-06-15 00:00:00

pages

1885-905

issue

11

eissn

0277-6715

issn

1097-0258

journal_volume

25

pub_type

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