Parceling Cannot Reduce Factor Indeterminacy in Factor Analysis: A Research Note

Edward E. Rigdon (), Jan-Michael Becker and Marko Sarstedt
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Edward E. Rigdon: Georgia State University
Jan-Michael Becker: University of Cologne
Marko Sarstedt: Otto-von-Guericke-University Magdeburg

Psychometrika, 2019, vol. 84, issue 3, No 6, 772-780

Abstract: 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.

Keywords: factor analysis; parceling; factor indeterminacy; uncertainty (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11336-019-09677-2

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