Testing independence between two Poisson-generated multinomial variables in case-series and cohort studies

In case‐series or cohort studies, we propose a test of independence between the occurrences of two types of recurrent events (such as two repeated infections) related to an intermittent exposure (such as an antibiotic treatment). The test relies upon an extension of a recent method for analysing cas...

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Bibliographic Details
Published in:Statistics in medicine 2005-12, Vol.24 (24), p.4035-4044
Main Authors: Hocine, Mounia, Guillemot, Didier, Tubert-Bitter, Pascale, Moreau, Thierry
Format: Article
Language:English
Subjects:
Anti-Bacterial Agents - pharmacology
bacterial resistance
beta-Lactams - pharmacology
bivariate multinomial
case-series
Child
Child, Preschool
cohort
Cohort Studies
conditional likelihood
France
Humans
Life Sciences
Methodology
Pharyngeal Diseases - drug therapy
Poisson Distribution
recurrent events
Santé publique et épidémiologie
Statistics
Streptococcus pneumoniae - drug effects
Streptococcus pneumoniae - growth & development
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Summary:In case‐series or cohort studies, we propose a test of independence between the occurrences of two types of recurrent events (such as two repeated infections) related to an intermittent exposure (such as an antibiotic treatment). The test relies upon an extension of a recent method for analysing case‐series data, in the presence of one type of recurrent event. The test statistic is derived from a bivariate Poisson generated‐multinomial distribution. Simulations for checking the validity of the test concerning the type I error and the power properties are presented. The test is illustrated using data from a cohort on antibiotics bacterial resistance in schoolchildren. Copyright © 2005 John Wiley & Sons, Ltd.
ISSN:0277-6715
1097-0258
DOI:10.1002/sim.2413