, Volume 84, Issue 3, pp 772–780 | Cite as

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

  • Edward E. RigdonEmail author
  • Jan-Michael Becker
  • Marko Sarstedt


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.


factor analysis parceling factor indeterminacy uncertainty 


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© The Psychometric Society 2019

Authors and Affiliations

  1. 1.Georgia State UniversityAtlantaUSA
  2. 2.University of CologneCologneGermany
  3. 3.Otto-von-Guericke-University MagdeburgMagdeburgGermany
  4. 4.School of Business and GA21Monash University MalaysiaSubang JayaMalaysia

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