Context: Age, period and birth cohort (APC) effects have been known for decades in biological, health and social sciences. However, exact collinearity between these three (Age = Year - Birth Year) leads to difficulty estimating these effects. It is thus impossible to estimate linear components of these effects without strong assumptions about at least one of these. This is problematic for anyone interested in APC patterns. Attempts to 'solve' this identification problem without strong assumptions are, in fact, making hidden unintended assumptions.Objective: Provide an overview of what APC effects are and the nature of the identification problem, before reviewing and critiquing methodological literature across the health and social sciences. I also present an argument for what researchers should do.Method: Non-systematic review of methodological literature across health and social sciences.Results: Recommendations include considering non-linearities around linear APC effects and stating strong and explicit theory-based assumptions. Mechanical solutions to the identification problem do not work.Conclusion: These recommendations acknowledge there is a 'line of solutions' of possible combinations of APC effects, and not a single answer that can be estimated empirically. None of these methods solve the identification problem - rather they acknowledge that methods are limited by assumptions.

中文翻译：

---

年龄群组分析：回顾我们应该做和不应该做的事。

背景：年龄，时期和出生队列（APC）的影响在生物学，健康和社会科学领域已有数十年的历史了。但是，这三个变量之间的精确共线性（年龄=年-出生年）导致难以估计这些影响。因此，如果没有关于这些影响中至少一个的强有力的假设，就不可能估计这些影响的线性成分。对于任何对APC模式感兴趣的人来说，这都是有问题的。试图在没有强力假设的情况下“解决”这个识别问题实际上是在做一些无意识的假设。目的：在回顾和批判健康和社会领域的方法学文献之前，概述一下APC的影响以及识别问题的性质。科学。我还提出了研究人员应该做什么的论点。结果：建议包括考虑线性APC效应周围的非线性问题，并陈述基于理论的强有力和明确的假设。结论：这些建议承认存在APC效应可能组合的“解决方案线”，而不是可以凭经验估算的单个答案。这些方法都不能解决识别问题-而是他们承认这些方法受假设限制。结论：这些建议承认存在APC效果可能组合的“解决方案”，而不是可以凭经验估计的单个答案。这些方法都不能解决识别问题-而是承认方法受假设限制。结论：这些建议承认存在APC效应可能组合的“解决方案”，而不是可以凭经验估算的单个答案。这些方法都不能解决识别问题-而是他们承认这些方法受假设限制。