A dynamic factor model for the analysis of multivariate time series

Research output: Contribution to journalArticle

259 Citations (Scopus)

Abstract

As a method to ascertain the structure of intra-individual variation, P-technique has met difficulties in the handling of a lagged covariance structure. A new statistical technique, coined dynamic factor analysis, is proposed, which accounts for the entire lagged covariance function of an arbitrary second order stationary time series. Moreover, dynamic factor analysis is shown to be applicable to a relatively short stretch of observations and therefore is considered worthwhile for psychological research. At several places the argumentation is clarified through the use of examples.

Original languageEnglish (US)
Pages (from-to)181-202
Number of pages22
JournalPsychometrika
Volume50
Issue number2
DOIs
StatePublished - Jun 1 1985

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Dynamic Factor Model
Multivariate Time Series
Factor analysis
Factor Analysis
Dynamic Analysis
Statistical Factor Analysis
Time series
P-variation
Stationary Time Series
Covariance Function
Argumentation
Covariance Structure
Stretch
Entire Function
Psychology
Arbitrary
Research
Observation

All Science Journal Classification (ASJC) codes

  • Psychology(all)
  • Applied Mathematics

Cite this

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A dynamic factor model for the analysis of multivariate time series. / Molenaar, Peter.

In: Psychometrika, Vol. 50, No. 2, 01.06.1985, p. 181-202.

Research output: Contribution to journalArticle

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