Journal article
Frailty models with applications to the study of infant deaths on birth timing in Ghana and Kenya
Quality & quantity, v 46(5), pp 1505-1521
01 Aug 2012
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In hazard models, it is assumed that all heterogeneity is captured by a set of theoretically relevant covariates. In many applications however, there are ample reasons for unobserved heterogeneity due to omitted or unmeasured factors. If there is unmeasured frailty, the hazard will not only be a function of the covariates but also of the unmeasured frailty. This paper discusses the implications of unobserved heterogeneity on parameter estimates with application to the analysis of infant death on subsequent birth timing in Ghana and Kenya using DHS data. Using Lognormal Accelerated Failure Time models with and without frailty, we found that standard models that do not control for unobserved heterogeneity produced biased estimates by overstating the degree of positive dependence and underestimating the degree of negative dependence. The implications of the findings are discussed.
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Details
- Title
- Frailty models with applications to the study of infant deaths on birth timing in Ghana and Kenya
- Creators
- Stephen Obeng Gyimah - Queen's UniversityAlex Ezeh - African Population and Health Research CenterJ. C. Fotso - African Population and Health Research Center
- Publication Details
- Quality & quantity, v 46(5), pp 1505-1521
- Publisher
- Springer Nature
- Number of pages
- 17
- Grant note
- Social Science and Humanities Research Council of Canada; Social Sciences and Humanities Research Council of Canada (SSHRC)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Community Health and Prevention
- Web of Science ID
- WOS:000305962200012
- Scopus ID
- 2-s2.0-84863552772
- Other Identifier
- 991020531992404721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Social Sciences, Interdisciplinary
- Statistics & Probability