Osmond C, Gardner M J
MRC Environmental Epidemiology Unit, Southampton General Hospital, England.
Am J Epidemiol. 1989 Jan;129(1):31-5. doi: 10.1093/oxfordjournals.aje.a115121.
Age, period, and cohort models have generally been applied to rates from tabulated national statistics, and it is known that such models suffer from an identification problem. When individual records, including date of birth, are available, however, a unique solution has been proposed which uses non-overlapping cohorts. We have shown that the identification problem exists in continuous time, so that even perfect information on the three variables will fail to resolve it. It is important to recognize clearly the assumptions that are implicit in the non-overlapping cohort formulation of the age-period-cohort model. The value of the solution proposed depends critically on their appropriateness or otherwise. It should always be remembered that the assumptions determine much of the final solution, including the apportionment of trend to the different components, age, period, or cohort.
年龄、时期和队列模型通常应用于表格形式的国家统计数据中的比率，并且已知此类模型存在识别问题。然而，当包括出生日期在内的个人记录可用时，有人提出了一种使用非重叠队列的独特解决方案。我们已经表明，识别问题在连续时间中存在，因此即使关于这三个变量的信息完美也无法解决该问题。重要的是要清楚认识到年龄-时期-队列模型的非重叠队列公式中隐含的假设。所提出的解决方案的价值关键取决于这些假设是否合适。应该始终记住，这些假设在很大程度上决定了最终的解决方案，包括趋势在不同组成部分（年龄、时期或队列）之间的分配。
