Multidimensionality and Structural Coefficient Bias in Structural Equation Modeling

By S. Reise, Richard Scheines, K. Widaman, Mark G. Haviland. 2013

698 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems and Management, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/aff372def4c16597f1c43bd02d1a8fd266e86978

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Rob R. Meijer
2. K. Neff
3. Wes Bonifay
4. Mark G. Haviland
5. S. Reise
6. Richard Scheines
7. Anthony Rodriguez
8. Alexandre J. S. Morin

In Information Systems and Management

1. S. Reise
2. Mark G. Haviland
3. Richard Scheines
4. K. Neff

In Management Science and Operations Research

1. Rob R. Meijer
2. Mark G. Haviland
3. S. Reise
4. K. Neff
5. Wes Bonifay
6. Richard Scheines
7. Anthony Rodriguez
8. Alexandre J. S. Morin

Citations in the corpus

• Does Self-Compassion Entail Reduced Self-Judgment, Isolation, and Over-Identification? A Response to Muris, Otgaar, and Petrocchi (2016) (2016, background): “Perhaps the authors meant to reference Reise et al. (2013), who do discuss the fact that measures with a larger number of subscale factors can lead to structural coefficient bias.”
• Applying Bifactor Statistical Indices in the Evaluation of Psychological Measures (2016, background): “A straightforward measure of degree of essential unidimensionality is the ECV (Reise et al., 2013; Sijtsma, 2009; ten Berge & So can, 2004; Stucky & Edelen, 2014; Stucky et al., 2013).”
• When Are Multidimensional Data Unidimensional Enough for Structural Equation Modeling? An Evaluation of the DETECT Multidimensionality Index (2015, methodology): “Table 5 shows that ECV and PUC are related to absolute bias (r = –.60 and r = –.68, respectively) and to relative bias (r = –.70 and r = –.54, respectively).”