Publication | Closed Access
Analyzing reciprocal relationships by means of the continuous‐time autoregressive latent trajectory model
27
Citations
59
References
2008
Year
Social PsychologyIndividual DifferencesEducationMental HealthReciprocal RelationshipsPsychologyTime Series EconometricsSocial SciencesReciprocal RelationsLatent ModelingDance MediaStochastic ProcessesLatent TrajectoryStatisticsStructural Equation ModelingNonlinear Time SeriesLatent Variable MethodsBollen New MethodsLatent Variable ModelPsychosocial FactorApplied Social PsychologyMultilevel ModelingMarginal Structural ModelsPsychosocial ResearchPsychosocial IssueSociologyInterpersonal RelationshipsEconometricsTime-varying ConfoundingTemporal NetworkSpatio-temporal Model
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.
| Year | Citations | |
|---|---|---|
Page 1
Page 1