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Dynamic analysis of recurrent event data with missing observations, with application to infant diarrhoea in Brazil

Lookup NU author(s): Professor Ornulf Borgan, Professor Robin Henderson

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Abstract

This paper examines and applies methods for modelling longitudinal binary data subject to both intermittent missingness and dropout. The paper is based around the analysis of data from a study into the health impact of a sanitation programme carried out in Salvador, Brazil. Our objective was to investigate risk factors associated with incidence and prevalence of diarrhoea in children aged up to 3 years old. In total, 926 children were followed up at home twice a week from October 2000 to January 2002 and for each child daily occurrence of diarrhoea was recorded. A challenging factor in analysing these data is the presence of between-subject heterogeneity not explained by known risk factors, combined with significant loss of observed data through either intermittent missingness (average of 78 days per child) or dropout (21% of children). We discuss modelling strategies and show the advantages of taking an event history approach with an additive discrete time regression model.


Publication metadata

Author(s): Borgan O, Fiaccone RL, Henderson R, Barreto ML

Publication type: Article

Publication status: Published

Journal: Scandinavian Journal of Statistics

Year: 2007

Volume: 34

Issue: 1

Pages: 53-69

ISSN (print): 0303-6898

ISSN (electronic): 1467-9469

Publisher: Wiley-Blackwell

URL: http://dx.doi.org/10.1111/j.1467-9469.2006.00525.x

DOI: 10.1111/j.1467-9469.2006.00525.x


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