%0 Journal Article %1 voelkle2012approach %A Voelkle, Manuel C %A Oud, Johan H L %A Davidov, Eldad %A Schmidt, Peter %D 2012 %I American Psychological Association %J Psychological Methods %K continuous cross-lagged design;autoregressive differential equations; model modeling; panel stochastic time %N 2 %P 176--192 %T An SEM approach to continuous time modeling of panel data: Relating authoritarianism and anomia %U http://www.zora.uzh.ch/63110/1/Voelkle_Oud_Davidov_Schmidt_Psychological_Methods.pdf %V 17 %X 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.

@article{voelkle2012approach, abstract = {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.}, added-at = {2013-03-29T17:50:10.000+0100}, author = {Voelkle, Manuel C and Oud, Johan H L and Davidov, Eldad and Schmidt, Peter}, biburl = {https://www.bibsonomy.org/bibtex/27ae60f73d73fd575c18151b165f62334/stef1313}, interhash = {daface01752320756c000c5447420d1b}, intrahash = {7ae60f73d73fd575c18151b165f62334}, journal = {Psychological Methods}, keywords = {continuous cross-lagged design;autoregressive differential equations; model modeling; panel stochastic time}, note = {This article may not exactly replicate the final version published in the APA journal. It is not the copy of record. Copyright: American Psychological Association}, number = 2, pages = {176--192}, publisher = {American Psychological Association}, timestamp = {2013-03-29T17:50:10.000+0100}, title = {An SEM approach to continuous time modeling of panel data: Relating authoritarianism and anomia}, url = {http://www.zora.uzh.ch/63110/1/Voelkle_Oud_Davidov_Schmidt_Psychological_Methods.pdf}, volume = 17, year = 2012 }