Job performance as multivariate dynamic criteria: Experience sampling and multiway component analysis

Seth M. Spain, Andrew G. Miner, Pieter M. Kroonenberg, Fritz Drasgow

Research output: Contribution to journalArticlepeer-review

Abstract

Questions about the dynamic processes that drive behavior at work have been the focus of increasing attention in recent years. Models describing behavior at work and research on momentary behavior indicate that substantial variation exists within individuals. This article examines the rationale behind this body of work and explores a method of analyzing momentary work behavior using experience sampling methods. The article also examines a previously unused set of methods for analyzing data produced by experience sampling. These methods are known collectively as multiway component analysis. Two archetypal techniques of multimode factor analysis, the Parallel factor analysis and the Tucker3 models, are used to analyze data from Miner, Glomb, and Hulin's (2010) experience sampling study of work behavior. The efficacy of these techniques for analyzing experience sampling data is discussed as are the substantive multimode component models obtained.

Original languageEnglish (US)
Pages (from-to)599-626
Number of pages28
JournalMultivariate Behavioral Research
Volume45
Issue number4
DOIs
StatePublished - Aug 27 2010

ASJC Scopus subject areas

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

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