Multistate models of postpartum infecundity, fecundability and sterility by age and parity: Methodological issues

Anatoli Yashin, Ivan Iachine, Kirill Andreev and Ulla Larsen

Mathematical Population Studies, 1998, vol. 7, issue 1, 51-78

Abstract: How do hidden physiological processes influence estimates of fecundability and sterility? Does unobserved heterogeneity play a role in these estimates? To address these questions mathematical models of the reproductive process are needed. It is not well known how to evaluate characteristics of reproductive models based on observed reproductive history data, and such models may not be identifiable without ancillary information. However, little is known about how to introduce ancillary information into reproductive models. Furthermore, even if such information was involved, the use of standard software packages for maximization of the likelihood function is often not feasible, because the function cannot be represented in an explicit parametric form. In this paper we propose an approach which represents the likelihood function in a form useful for further analysis. This approach is based on multistate models of the basic physiological processes that influence reproductive outcomes, and it is suitable in applications where ancillary information is given in the form of hazard rates. As an alternative, a competing risks model with incomplete information is discussed.

Keywords: Reproductive history models; Unobserved heterogeneity; Fertility Submitted by C.M. Suchindran (search for similar items in EconPapers)
Date: 1998
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/08898489809525446 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:mpopst:v:7:y:1998:i:1:p:51-78

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GMPS20

DOI: 10.1080/08898489809525446

Access Statistics for this article

Mathematical Population Studies is currently edited by Prof. Noel Bonneuil, Annick Lesne, Tomasz Zadlo, Malay Ghosh and Ezio Venturino

More articles in Mathematical Population Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().