Abstract
Investigating the impact of important risk factors and geographical location on child morbidity and malnutrition is of high relevance for developing countries. Previous research has usually carried out separate regression analyses for certain diseases or types of malnutrition, neglecting possible association between them. Based on data from the Nigeria Demographic and Health Survey of 2003, we apply recently developed geoadditive latent variable models, taking cough, fever and diarrhea as well as stunting and underweight as observable indicators for the latent variables morbidity and mortality. This allows to study the common impact of risk factors and geographical location on these latent variables, thereby taking account of association within a joint model. Our analysis identifies socio-economic and public health factors, nonlinear effects of age and other continuous covariates as well as spatial effects jointly influencing morbidity and malnutrition.
Dokumententyp: | Paper |
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Keywords: | Developing countries, geoadditive regression, latent variable models, child morbidity, mortality |
Fakultät: | Mathematik, Informatik und Statistik > Statistik > Technische Reports |
URN: | urn:nbn:de:bvb:19-epub-2368-4 |
Sprache: | Englisch |
Dokumenten ID: | 2368 |
Datum der Veröffentlichung auf Open Access LMU: | 19. Mrz. 2008, 13:15 |
Letzte Änderungen: | 04. Nov. 2020, 12:46 |