Hierarchical multistate models from population data: an application to parity statuses

基于人口数据的分层多状态模型:以胎次状态为例

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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 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.

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