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Demographic models of the reproductive process: Past, interlude, and future.
Ciganda, Daniel; Todd, Nicolas.
Afiliação
  • Ciganda D; Max Planck Institute for Demographic Research.
  • Todd N; Max Planck Institute for Demographic Research.
Popul Stud (Camb) ; 76(3): 495-513, 2022 11.
Article em En | MEDLINE | ID: mdl-34486942
ABSTRACT
After 30 years of active development, mechanistic models of the reproductive process nearly stopped attracting scholarly interest in the early 1980s. In the following decades, fertility research continued to thrive, relying on solid descriptive work and detailed analysis of micro-level data. The absence of systematic modelling efforts, however, has also made the field more fragmented, with empirical research, theory building, and forecasting advancing along largely disconnected channels. In this paper we outline some of the drivers of this process, from the popularization of user-friendly statistical software to the limitations of early family building models. We then describe a series of developments in computational modelling and statistical computing that can contribute to the emergence of a new generation of mechanistic models. Finally, we introduce a concrete example of this new kind of model, and show how they can be used to formulate and test theories coherently and make informed projections.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fertilidade Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fertilidade Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article