On the Intrinsic Estimator and Constrained Estimators in Age-Period-Cohort Models
On the Intrinsic Estimator and Constrained Estimators in Age-Period-Cohort Models
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DOI：
10.1177/0049124111415355
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发表时间：
2011-08-01
影响因子：
6.3
通讯作者：
Yang, Yang
中科院分区：
文献类型：
--
作者：
Fu, Wenjiang J.;Land, Kenneth C.;Yang, Yang
在研究事件的时间排序率时，流行病学家、人口学家和社会科学家经常发现区分三个不同的时间维度是有用的，即年龄（参与者的年龄）、时间段（记录感兴趣事件的日历年或其他时间段）和队列（出生队列或世代）。同期队列（APC）分析旨在分析特定年龄年份的存档事件发生率，以捕获所调查事件的时间趋势。然而，在比率表的背景下，这三个因素之间的众所周知的关系，时期-年龄=队列，使得APC多分类模型的参数估计困难。参数估计的辨识问题自20世纪70年代以来一直在研究，至今仍存在争议。在这方面的最新发展包括内在估计（IE）方法，自回归队列模型，年龄-时期-队列特征（APCC）模型，回归样条模型，平滑队列模型和分层APC模型。奥布莱恩（2011年），第100页。419452，this issue）在研究APC模型中的约束估计，特别是IE方面做出了进一步的贡献。作者，但是，有重要的分歧与奥布莱恩的统计性质的IE是什么，以及如何估计从IE应解释。作者指出了这些分歧，以结束文章。
In studying temporally ordered rates of events, epidemiologists, demographers, and social scientists often find it useful to distinguish three different temporal dimensions, namely, age (age of the participants involved), time period (the calendar year or other temporal period for recording the events of interest), and cohort (birth cohort or generation). Age-period-cohort (APC) analysis aims to analyze age-year-specific archived event rates to capture temporal trends in the events under investigation. However, in the context of tables of rates, the well-known relationship among these three factors, Period - Age = Cohort, makes the parameter estimation of the APC multiple classification model difficult. The identification problem of the parameter estimation has been studied since the 1970s and still remains in debate. Recent developments in this regard include the intrinsic estimator (IE) method, the autoregressive cohort model, the age-period-cohort-characteristic (APCC) model, the regression splines model, the smoothing cohort model, and the hierarchical APC model. O'Brien (2011; pp. 419452, this issue) makes a further contribution in studying constrained estimators, particularly the IE, in the APC models. The authors, however, have important disagreements with O'Brien as to what the statistical properties of the IE are and how the estimates from the IE should be interpreted. The authors point out these disagreements to conclude the article.