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参数和非参数生命历程分析:在家庭形成模式中的应用。

Parametric and nonparametric analysis of life courses: an application to family formation patterns.

机构信息

Department of Policy Analysis and Public Management, Bocconi University, via Röntgen 1, 20136, Milan, Italy.

出版信息

Demography. 2013 Jun;50(3):881-902. doi: 10.1007/s13524-012-0191-z.

Abstract

We discuss a unified approach to the description and explanation of life course patterns represented as sequences of states observed in discrete time. In particular, we study life course data collected as part of the Dutch Fertility and Family Surveys (FFS) to learn about the family formation behavior of 1,897 women born between 1953 and 1962. Retrospective monthly data were available on each 18- to 30-year-old woman living either with or without children as single, married, or cohabiting. We first study via a nonparametric approach which factors explain the pairwise dissimilarities observed between life courses. Permutation distribution inference allows for the study of the statistical significance of the effect of a set of covariates of interest. We then develop a parametric model for the sequence-generating process that can be used to describe state transitions and durations conditional on covariates and conditional on having observed an initial segment of the trajectory. Fitting of the proposed model and the corresponding model selection process are based on the observed data likelihood. We discuss the application of the methods to the FFS.

摘要

我们讨论了一种统一的方法,用于描述和解释以离散时间观测到的状态序列表示的生命历程模式。特别是,我们研究了作为荷兰生育与家庭调查(FFS)一部分收集的生命历程数据,以了解 1953 年至 1962 年间出生的 1897 名女性的家庭形成行为。回溯性的每月数据可用于记录每个 18 至 30 岁的女性,她们或与子女同住,或单身、已婚或同居。我们首先通过非参数方法研究了哪些因素可以解释生命历程中观察到的成对差异。置换分布推断允许研究一组感兴趣的协变量的影响的统计显著性。然后,我们为序列生成过程开发了一个参数模型,该模型可用于描述状态转换和持续时间,条件是协变量和观测到轨迹的初始段。所提出模型的拟合和相应的模型选择过程基于观测数据似然。我们讨论了该方法在 FFS 中的应用。

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