Universität zu Köln

Rigdon, Edward E., Becker, Jan-Michael ORCID: 0000-0003-3013-3739 and Sarstedt, Marko ORCID: 0000-0002-5424-4268 (2019). Parceling Cannot Reduce Factor Indeterminacy in Factor Analysis: A Research Note. Psychometrika, 84 (3). S. 772 - 781. NEW YORK: SPRINGER. ISSN 1860-0980

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Abstract

Parceling-using composites of observed variables as indicators for a common factor-strengthens loadings, but reduces the number of indicators. Factor indeterminacy is reduced when there are many observed variables per factor, and when loadings and factor correlations are strong. It is proven that parceling cannot reduce factor indeterminacy. In special cases where the ratio of loading to residual variance is the same for all items included in each parcel, factor indeterminacy is unaffected by parceling. Otherwise, parceling worsens factor indeterminacy. While factor indeterminacy does not affect the parameter estimates, standard errors, or fit indices associated with a factor model, it does create uncertainty, which endangers valid inference.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Rigdon, Edward E. UNSPECIFIED UNSPECIFIED UNSPECIFIED Becker, Jan-Michael UNSPECIFIED orcid.org/0000-0003-3013-3739 UNSPECIFIED Sarstedt, Marko UNSPECIFIED orcid.org/0000-0002-5424-4268 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-143680
DOI:	10.1007/s11336-019-09677-2
Journal or Publication Title:	Psychometrika
Volume:	84
Number:	3
Page Range:	S. 772 - 781
Date:	2019
Publisher:	SPRINGER
Place of Publication:	NEW YORK
ISSN:	1860-0980
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language INDICATORS; STRATEGIES; REGRESSION; VARIABLES Multiple languages Mathematics, Interdisciplinary Applications; Social Sciences, Mathematical Methods; Psychology, Mathematical Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/14368