Cross-Temporal Meta-Analysis: A Conceptual and Empirical Critique

The proper estimation of age, period, and cohort (APC) effects is a pervasive concern for the study of a variety of psychological and social phenomena, inside and outside of organizations. One analytic technique that has been used to estimate APC effects is cross-temporal meta-analysis (CTMA). Although CTMA has some appealing qualities (e.g., ease of interpretability), it has also been criticized on theoretical and methodological grounds. Furthermore, CTMA makes strong assumptions about the nature and operation of cohort effects relative to age and period effects that have not been empirically tested. Accordingly, the goal of this paper is to explore CTMA, its history, and these assumptions. Using a Monte Carlo study, we demonstrate that, in many cases, cohort effects are misestimated (i.e., systematically over- or underestimated) by CTMA. This work provides further evidence that APC effects pose intractable problems for research questions where APC effects are of interest.