Job Performance as Multivariate Dynamic Criteria: Experience Sampling and Multiway Component Analysis

Autor/inn/en	Spain, Seth M.; Miner, Andrew G.; Kroonenberg, Pieter M.; Drasgow, Fritz
Titel	Job Performance as Multivariate Dynamic Criteria: Experience Sampling and Multiway Component Analysis
Quelle	In: Multivariate Behavioral Research, 45 (2010) 4, S.599-626 (28 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0027-3171
Schlagwörter	Job Performance; Factor Analysis; Sampling; Methods; Data Analysis; Employees + Suchen Sie Ihr Suchwort? Work performance; Arbeitsleistung; Faktorenanalyse; Method; Methode; Auswertung; Employee; Arbeitnehmer; Beschäftigter
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. (Contains 7 figures and 6 tables.) (As Provided).
Anmerkungen	Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10