"An SEM approach to continuous time modeling of panel data: Relating authoritarianism and anomia": Correction to Voelkle, Oud, Davidov, and Schmidt (2012).

Abstract

Reports an error in SEM approach to continuous time modeling of panel data: Relating authoritarianism and by Manuel C. Voelkle, Johan H. L. Oud, Eldad Davidov and Peter Schmidt (Psychological Methods, 2012[Jun], Vol 17[2], 176-192). The supplemental materials link was missing. All versions of this article have been corrected. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2012-09124-001.) Panel studies, in which the same subjects are repeatedly observed at multiple time points, are among the most popular longitudinal designs in psychology. Meanwhile, there exists a wide range of different methods to analyze such data, with autoregressive and cross-lagged models being 2 of the most well known representatives. Unfortunately, in these models time is only considered implicitly, making it difficult to account for unequally spaced measurement occasions or to compare parameter estimates across studies that are based on different time intervals. Stochastic differential equations offer a solution to this problem by relating the discrete time model to its underlying model in continuous time. It is the goal of the present article to introduce this approach to a broader psychological audience. A step-by-step review of the relationship between discrete and continuous time modeling is provided, and we demonstrate how continuous time parameters can be obtained via structural equation modeling. An empirical example on the relationship between authoritarianism and anomia is used to illustrate the approach.