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| author_facet |
Schoen, Robert Schoen, Robert |
|---|---|
| author |
Schoen, Robert |
| spellingShingle |
Schoen, Robert PeerJ Hierarchical multistate models from population data: an application to parity statuses General Agricultural and Biological Sciences General Biochemistry, Genetics and Molecular Biology General Medicine General Neuroscience |
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schoen, robert |
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Schoen, Robert 2167-8359 PeerJ General Agricultural and Biological Sciences General Biochemistry, Genetics and Molecular Biology General Medicine General Neuroscience http://dx.doi.org/10.7717/peerj.2535 <jats:p>Hierarchical models are characterized by having<jats:italic>N</jats:italic>living states connected by<jats:italic>N</jats:italic>− 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 US 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.</jats:p> Hierarchical multistate models from population data: an application to parity statuses PeerJ |
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49 |
| title |
Hierarchical multistate models from population data: an application to parity statuses |
| title_unstemmed |
Hierarchical multistate models from population data: an application to parity statuses |
| title_full |
Hierarchical multistate models from population data: an application to parity statuses |
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Hierarchical multistate models from population data: an application to parity statuses |
| title_full_unstemmed |
Hierarchical multistate models from population data: an application to parity statuses |
| title_short |
Hierarchical multistate models from population data: an application to parity statuses |
| title_sort |
hierarchical multistate models from population data: an application to parity statuses |
| topic |
General Agricultural and Biological Sciences General Biochemistry, Genetics and Molecular Biology General Medicine General Neuroscience |
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http://dx.doi.org/10.7717/peerj.2535 |
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2016 |
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<jats:p>Hierarchical models are characterized by having<jats:italic>N</jats:italic>living states connected by<jats:italic>N</jats:italic>− 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 US 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.</jats:p> |
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| description | <jats:p>Hierarchical models are characterized by having<jats:italic>N</jats:italic>living states connected by<jats:italic>N</jats:italic>− 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 US 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.</jats:p> |
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| spelling | Schoen, Robert 2167-8359 PeerJ General Agricultural and Biological Sciences General Biochemistry, Genetics and Molecular Biology General Medicine General Neuroscience http://dx.doi.org/10.7717/peerj.2535 <jats:p>Hierarchical models are characterized by having<jats:italic>N</jats:italic>living states connected by<jats:italic>N</jats:italic>− 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 US 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.</jats:p> Hierarchical multistate models from population data: an application to parity statuses PeerJ |
| spellingShingle | Schoen, Robert, PeerJ, Hierarchical multistate models from population data: an application to parity statuses, General Agricultural and Biological Sciences, General Biochemistry, Genetics and Molecular Biology, General Medicine, General Neuroscience |
| title | Hierarchical multistate models from population data: an application to parity statuses |
| title_full | Hierarchical multistate models from population data: an application to parity statuses |
| title_fullStr | Hierarchical multistate models from population data: an application to parity statuses |
| title_full_unstemmed | Hierarchical multistate models from population data: an application to parity statuses |
| title_short | Hierarchical multistate models from population data: an application to parity statuses |
| title_sort | hierarchical multistate models from population data: an application to parity statuses |
| title_unstemmed | Hierarchical multistate models from population data: an application to parity statuses |
| topic | General Agricultural and Biological Sciences, General Biochemistry, Genetics and Molecular Biology, General Medicine, General Neuroscience |
| url | http://dx.doi.org/10.7717/peerj.2535 |