Hierarchical multistate models from population data: An application to parity statuses
- Published
- Accepted
- Subject Areas
- Public Health, Women's Health, Statistics
- Keywords
- multistate models, parity status life tables, childlessness, hierarchical models, sequential cross-sections, polytrees
- Copyright
- © 2016 Schoen
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2016. Hierarchical multistate models from population data: An application to parity statuses. PeerJ Preprints 4:e2128v1 https://doi.org/10.7287/peerj.preprints.2128v1
Abstract
Hierarchical models are characterized by having N living states connected by N–1 rates of transfer. Demographic measures for such models can be calculated directly from counts of the number of persons in each state at two nearby points in time. Exploiting the ability of population stocks to determine the flows in hierarchical models expands the range of demographic analysis.
The value of such analyses is illustrated by an application to childbearing, where the states of interest reflect the number of children a woman has born. Using Census data on the distribution of women by age and parity, a parity status life table for U.S. Women, 2005-2010, is constructed. That analysis shows that nearly a quarter of American women are likely to remain childless, with a 0-3 child pattern replacing the 2-4 child pattern of the past.
Author Comment
This is a submission to PeerJ for review.