Analyzing reciprocal relationships by means of the continuous-time autoregressive latent trajectory model
Version of Record online: 16 JAN 2008
Volume 62, Issue 1, pages 58–82, February 2008
How to Cite
Delsing, M. J. M. H. and Oud, J. H. L. (2008), Analyzing reciprocal relationships by means of the continuous-time autoregressive latent trajectory model. Statistica Neerlandica, 62: 58–82. doi: 10.1111/j.1467-9574.2007.00386.x
- Issue online: 16 JAN 2008
- Version of Record online: 16 JAN 2008
- Received: July 2007. Revised: October 2007.
- continuous time modeling;
- ALT model;
- exact discrete model;
- approximate discrete model;
- stochastic differential equation;
- reciprocal relations;
- structural equation modeling
Over the past decades, several analytic tools have become available for the analysis of reciprocal relations in a non-experimental context using structural equation modeling (SEM). The autoregressive latent trajectory (ALT) model is a recently proposed model [BOLLEN and CURRAN Sociological Methods and Research (2004) Vol. 32, pp. 336–383; CURRAN and BOLLEN New Methods for the Analysis of Change (2001) American Psychological Association, Washington, DC], which captures features of both the autoregressive (AR) cross-lagged model and the latent trajectory (LT) model. The present article discusses strengths and weaknesses and demonstrates how several of the problems can be solved by a continuous-time version: the continuous-time autoregressive latent trajectory (CALT) model. Using SEM to estimate the exact discrete model (EDM), the EDM/SEM continuous-time procedure is applied to a CALT model of reciprocal relations between antisocial behavior and depressive symptoms.