First- and Higher-Order Continuous Time Models for Arbitrary N Using SEM

Johan H. L. Oud (), Manuel C. Voelkle () and Charles C. Driver ()
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Johan H. L. Oud: University of Nijmegen, Behavioural Science Institute
Manuel C. Voelkle: Humboldt-Universität zu Berlin, Department of Psychology
Charles C. Driver: Max Planck Institute for Human Development

Chapter Chapter 1 in Continuous Time Modeling in the Behavioral and Related Sciences, 2018, pp 1-26 from Springer

Abstract: Abstract In this chapter we review continuous time series modeling and estimation by extended structural equation models (SEM) for single subjects and N > 1. First-order as well as higher-order models will be dealt with. Both will be handled by the general state space approach which reformulates higher-order models as first-order models. In addition to the basic model, the extensions of exogenous variables and traits (random intercepts) will be introduced. The connection between continuous time and discrete time for estimating the model by SEM will be made by the exact discrete model (EDM). It is by the EDM that the exact estimation procedure in this chapter differentiates from many approximate procedures found in the literature. The proposed analysis procedure will be applied to the well-known Wolfer sunspot data, an N = 1 time series that has been analyzed by several continuous time analysts in the past. The analysis will be carried out by ctsem, an R-package for continuous time modeling that interfaces to OpenMx, and the results will be compared to those reported in the previous studies.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-77219-6_1

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DOI: 10.1007/978-3-319-77219-6_1

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