Title

Multiple Indicator Stationary Time Series Models

Authors

Authors

S. A. Sivo

Comments

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Abbreviated Journal Title

Struct. Equ. Modeling

Keywords

PANEL; Mathematics, Interdisciplinary Applications; Social Sciences, ; Mathematical Methods

Abstract

This article is intended to complement previous research (Sivo, 1997; Sivo & Willson, 1998, in press) by discussing the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. Three practical considerations motivated this article. Unlike Marsh (1993), Sivo and Willson (2000) did not offer multiple indicator (latent order) equivalents to their autoregressive (AR), moving average (MA), and autoregressive-moving average (ARMA) models. Moreover, such models have yet to be discussed, despite Marsh's (1993) advocacy for multiple indicator models in general. Further motivating multiple indicator extensions of the AR, MA, and ARMA equivalent models is the fact that longitudinal studies often collect data on more than 1 related variable per occasion. Such multiple indicator models capitalize on 1 of the chief analytical advantages of structural equation modeling in that measurement error may be estimated directly.

Journal Title

Structural Equation Modeling-a Multidisciplinary Journal

Volume

8

Issue/Number

4

Publication Date

1-1-2001

Document Type

Article

Language

English

First Page

599

Last Page

612

WOS Identifier

WOS:000208064800005

ISSN

1070-5511

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