The Use of Item-Parcels in CFAs (Confirmatory Factor Analyses) to Camouflage Misfit at the Item Level: Do Two Wrongs Make a Right?

• In Event: Advanced Topics in Structural Equation Modeling

Abstract

In SEM studies, it is typically ill-advised to:
(a) retain an independent clusters confirmatory factor analysis (ICM-CFA) model when its assumption of undimensionality is violated (i.e., there are no cross-loadings or correlated uniquenesses); and
(b) use item parcels when an ICM-CFA model does not fit the data.
However, the combined use of (a) and (b) often provides such misleadingly good fit indexes that applied researchers believe that misspecification problems are resolved—that two wrongs really do make a right.
In three studies based on real (self-esteem and big-five personality) and simulated data, we show that the use of item parcels can – and typically does:
• substantially inflate the apparent goodness of fit
• bias substantive interpretations of the results

Authors

• Herbert W. Marsh, University of Western Sydney

• Oliver Lüdtke, Tuebingen University

• Benjamin Nagengast, Tuebingen University

• Alexandre J.S. Morin, University of Sherbrooke

• Ulrich Trautwein, Universitat Tubingen

• Matthias Von Davier, ETS