Statistical modeling of the individual: Rationale and application of multivariate stationary time series analysis

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

Research output: Contribution to journalArticlepeer-review

121 Scopus citations

Abstract

Results obtained with interindividual techniques in a representative sample of a population are not necessarily generalizable to the individual members of this population. In this article the specific condition is presented that must be satisfied to generalize from the interindividual level to the intraindividual level. A way to investigate whether this condition is satisfied is by means of multivariate time series analysis. More generally, time series analysis can be used to investigate psychological processes situated within individuals. In this article we consider a well established class of multivariate stationary time series models that may be used to study the intraindividual covariance structure. We demonstrate the application of some of these models with an empirical example consisting of state measurements of behavior associated with the Five Factor Model of Personality. We illustrate how one can investigate whether individuals are similar with respect to their intraindividual structure of variation, and whether this structure is similar to the structure of interindividual variation.

Original languageEnglish (US)
Pages (from-to)207-233
Number of pages27
JournalMultivariate Behavioral Research
Volume40
Issue number2
DOIs
StatePublished - Nov 29 2005

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)

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