Bayes analysis of abridged age specific fertility pattern using parametric models

Rahul Kumar Mishra and Satyanshu K. Upadhyay

Communications in Statistics - Theory and Methods, 2022, vol. 51, issue 16, 5505-5533

Abstract: The paper provides a Bayesian alternative to transform the abridged age-specific fertility data into an unabridged one. A model suitable for a binary type of fertility data is considered for the study. The success probabilities of the considered model are assumed to vary in accordance with some established parametric age-specific fertility models. Bayes analysis is done using uniform priors for the unknown parameters of the considered models. Since the posterior analysis involves analytically intractable form of integrals, the paper employs the Gibbs sampler algorithm with intermediate Metropolis-Hastings steps to draw the corresponding posterior samples. Numerical illustration is provided using grouped age-specific fertility rate data. Finally, a few standard Bayesian model comparison tools are used in order to recommend an appropriate model for the data in hand, keeping in view the intended objectives.

Date: 2022
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DOI: 10.1080/03610926.2020.1843052

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