dc.creator | Borgan, Ørnulf | |
dc.creator | Fiaccone, Rosemeire Leovigildo | |
dc.creator | Henderson, Robin | |
dc.creator | Barreto, Mauricio Lima | |
dc.creator | Borgan, Ørnulf | |
dc.creator | Fiaccone, Rosemeire Leovigildo | |
dc.creator | Henderson, Robin | |
dc.creator | Barreto, Mauricio Lima | |
dc.date.accessioned | 2022-10-07T19:13:27Z | |
dc.date.available | 2022-10-07T19:13:27Z | |
dc.date.issued | 2007 | |
dc.identifier | 0303-6898 | |
dc.identifier | http://repositorio.ufba.br/ri/handle/ri/14715 | |
dc.identifier | v. 34, n. 1 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/4013177 | |
dc.description.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. | |
dc.language | en | |
dc.rights | Acesso Aberto | |
dc.source | http://dx.doi.org/10.1111/j.1467-9469.2006.00525.x | |
dc.subject | Additive regression model | |
dc.subject | Diarrhoea incidence and prevalence | |
dc.subject | Discrete time martingales | |
dc.subject | Dropout | |
dc.subject | Longitudinal binary data | |
dc.subject | Missing data | |
dc.title | Dynamic analysis of recurrent event data with missing observations, with application to infant diarrhoea in Brazil | |
dc.type | Artigo de Periódico | |