Frailty modeling for clustered survival data: an application to birth interval in Bangladesh

The present work demonstrates an application of random effects model for analyzing birth intervals that are clustered into geographical regions. Observations from the same cluster are assumed to be correlated because usually they share certain unobserved characteristics between them. Ignoring the co...

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Bibliographic Details
Published in:Journal of applied statistics 2013-12, Vol.40 (12), p.2670-2680
Main Authors: Mahmood, Sharif, Zainab, Begum, Latif, A.H.M. Mahbub
Format: Article
Language:English
Subjects:
Applied statistics
Birth
birth interval
Births
Clustering
correlated survival data
Correlation
Correlation analysis
Demographics
Demography
Intervals
Mathematical models
Parameter estimation
proportional hazards model
random effects model
residual maximum likelihood
Socioeconomic factors
Studies
Survival
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Summary:The present work demonstrates an application of random effects model for analyzing birth intervals that are clustered into geographical regions. Observations from the same cluster are assumed to be correlated because usually they share certain unobserved characteristics between them. Ignoring the correlations among the observations may lead to incorrect standard errors of the estimates of parameters of interest. Beside making the comparisons between Cox's proportional hazards model and random effects model for analyzing geographically clustered time-to-event data, important demographic and socioeconomic factors that may affect the length of birth intervals of Bangladeshi women are also reported in this paper.
ISSN:0266-4763
1360-0532
DOI:10.1080/02664763.2013.825702