ARMA-Based SEM When the Number of Time Points T Exceeds the Number of Cases N

Raw Data Maximum Likelihood

Ellen L. Hamaker, Conor V. Dolan, Peter Molenaar

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Longitudinal structural equation modeling has generally addressed the time-dependent covariance structure of a relatively small number of repeated measures, T, observed in a relatively large representative sample, N. In contrast, the literature on autoregressive moving average modeling is usually directed at a single realization comprising many observations, that is, N = 1, and T > 50. This article deals with autoregressive moving average-based structural equation modeling of time series data, in the situation that N is small, T is intermediate, and T > N. The aims of this article are to (a) give a brief overview of the development of alternative formulations of the likelihood function to obtain estimates of autoregressive moving average parameters, in particular the formulation that lies at the basis of Mélard's algorithm; (b) show the equivalence between the likelihood function to obtain estimates for these parameters, and the raw data likelihood method that can be used in structural equation modeling programs like Mx, and demonstrate this equivalence through simulation experiments; and (c) provide illustrations of this use of Mx with real data.

Original languageEnglish (US)
Pages (from-to)352-379
Number of pages28
JournalStructural Equation Modeling
Volume10
Issue number3
DOIs
StatePublished - Dec 1 2003

Fingerprint

Structural Equation Modeling
Autoregressive Moving Average
Maximum likelihood
Maximum Likelihood
Exceed
Likelihood Function
equivalence
Scanning electron microscopy
Equivalence
Time series
Repeated Measures
Formulation
Likelihood Methods
Covariance Structure
Time Series Data
Estimate
Simulation Experiment
time series
simulation
Experiments

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Modeling and Simulation
  • Sociology and Political Science
  • Economics, Econometrics and Finance(all)

Cite this

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ARMA-Based SEM When the Number of Time Points T Exceeds the Number of Cases N : Raw Data Maximum Likelihood. / Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter.

In: Structural Equation Modeling, Vol. 10, No. 3, 01.12.2003, p. 352-379.

Research output: Contribution to journalArticle

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