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统计年龄-时期-队列分析:综述与批判

Statistical age-period-cohort analysis: a review and critique.

作者信息

Kupper L L, Janis J M, Karmous A, Greenberg B G

出版信息

J Chronic Dis. 1985;38(10):811-30. doi: 10.1016/0021-9681(85)90105-5.

Abstract

Descriptive and statistical age-period-cohort (APC) analysis methods have received considerable attention in the literature. The statistical modeling of APC data often involves the popular multiple classification model, a model containing the effects of age groups (rows), periods of observation (columns), and birth cohorts (diagonals of the age-by-period table). The identifiability problem inherent to this model is discussed, and its adverse effects on the results of APC modeling exercises are illustrated numerically. Potential problems attendant with the use of two-factor models are described, and other possible modeling approaches currently in use are discussed. Interpretational limitations due to certain innate characteristics of typical APC data sets are also detailed. Given all the documented potential sources for error, the current state-of-the-art regarding the statistical modeling of APC data should be considered to be at an early stage of development.

摘要

描述性和统计性的年龄-时期-队列(APC)分析方法在文献中受到了相当多的关注。APC数据的统计建模通常涉及流行的多重分类模型,该模型包含年龄组(行)、观察时期(列)和出生队列(年龄-时期表的对角线)的效应。讨论了该模型固有的可识别性问题,并通过数值说明了其对APC建模练习结果的不利影响。描述了使用双因素模型伴随的潜在问题,并讨论了当前正在使用的其他可能的建模方法。还详细阐述了由于典型APC数据集的某些固有特征而导致的解释局限性。鉴于所有已记录的潜在误差来源,应认为APC数据统计建模的当前技术水平尚处于早期发展阶段。

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