A dynamic factor model for the analysis of multivariate time series

Peter C.M. Molenaar

Research output: Contribution to journalArticlepeer-review

343 Scopus citations


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
Issue number2
StatePublished - Jun 1985

All Science Journal Classification (ASJC) codes

  • General Psychology
  • Applied Mathematics


Dive into the research topics of 'A dynamic factor model for the analysis of multivariate time series'. Together they form a unique fingerprint.

Cite this