Van Hook Jennifer, Altman Claire E
The Pennsylvania State University, 601 Oswald Tower, University Park, PA 16802.
Popul Res Policy Rev. 2013 Aug 1;32(4):585-610. doi: 10.1007/s11113-013-9276-7.
Event history models, also known as hazard models, are commonly used in analyses of fertility. One drawback of event history models is that the conditional probabilities (hazards) estimated by event history models do not readily translate into summary measures, particularly for models of repeatable events, like childbirth. In this paper, we describe how to translate the results of discrete-time event history models of all births into well-known summary fertility measures: simulated age- and parity-specific fertility rates, parity progression ratios (PPRs), and the total fertility rate (TFR). The method incorporates all birth intervals, but permits the hazard functions to vary across parities. It also can simulate values for groups defined by both fixed and time-varying covariates, such as marital or employment life histories. We demonstrate the method using an example from the National Survey of Family Growth (NSFG) and provide an accompanying data file and Stata program.
事件史模型，也称为风险模型，常用于生育分析。事件史模型的一个缺点是，由事件史模型估计的条件概率（风险）不容易转化为汇总指标，特别是对于可重复事件的模型，如分娩。在本文中，我们描述了如何将所有出生的离散时间事件史模型的结果转化为著名的汇总生育指标：模拟的年龄和胎次别生育率、胎次递进比（PPR）和总和生育率（TFR）。该方法纳入了所有生育间隔，但允许风险函数因胎次而异。它还可以模拟由固定和随时间变化的协变量定义的群体的值，如婚姻或就业生活史。我们使用来自全国家庭成长调查（NSFG）的一个例子演示了该方法，并提供了一个配套的数据文件和Stata程序。
