Dynamic Analysis of Recurrent Event Data with Missing Observations, with Application to Infant Diarrhoea in Brazil |
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| Authors: | Ø RNULF BORGAN,ROSEMEIRE L. FIACCONE,ROBIN HENDERSON, MAURICIO L. BARRETO |
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| Affiliation: | Department of Mathematics, University of Oslo; Departamento de Estatistica, Universidade Federal da Bahia; School of Mathematics and Statistics, University of Newcastle upon Tyne; Instituto de Sa'ude Coletiva, Universidade Federal da Bahia |
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| Abstract: | 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. |
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| Keywords: | additive regression model diarrhoea incidence and prevalence discrete time martingales dropout longitudinal binary data missing data |
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