Efficient theory development and factor retention criteria: Abandon the ‘eigenvalue greater than one’ criterion

By V. Patil, Surendra N. Singh, S. Mishra, D. Donavan. 2008

307 citations recorded by the source corpus.

Subfields: Food Science, Marketing, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/d59439401b94704ec2c540d99bd36c5b1d0079af

How researchers see this paper

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

In Food Science

1. L. E. Garrido
2. F. J. Abad
3. Matt C. Howard
4. Vicente Ponsoda
5. Eric Tate

In Marketing

1. Matt C. Howard

In Organizational Behavior and Human Resource Management

1. Matt C. Howard
2. Tom Buchanan
3. Rebecca J. Bennett
4. Osman M. Karatepe

Citations in the corpus

• Performance of Velicer’s Minimum Average Partial Factor Retention Method With Categorical Variables (2011, methodology): “In addition, this procedure is currently recommended in ‘‘best practice’’ EFA guidelines (i.e., Hayton et al., 2004; Henson & Roberts, 2006; Patil et al., 2008), and its use has been increasing in recent years because of the availability of Figure 4.”
• Social vulnerability indices: a comparative assessment using uncertainty and sensitivity analysis (2012, background): “However, recent studies have shown that use of the Kaiser criterion overestimates the number of factors to retain, lending outsized importance to inconsequential factors (O’Connor 2000; Patil et al. 2008).”
• An Investigation into the Effects of Work–Family Conflict and Job Satisfaction on Salesperson Deviance (2010, background): “Recent research indicates that the practice of ignoring EFA procedures and proceeding directly to CFA may lead to “the development of non-parsimonious theories based on superfluous constructs” (Patil et al. 2008, p. 162).”
• Factors affecting faculty use of learning technologies: implications for models of technology adoption (2013, methodology): “Accordingly, we conducted a parallel analysis (Horn 1965) using the procedures and method outlined by Patil et al. (2008) where one compares ‘‘the 95th percentile eigenvalues of several random correlation matrices with the corresponding eigenvalue from the researcher’s dataset’’ (p. 164).”
• A Review of Exploratory Factor Analysis Decisions and Overview of Current Practices: What We Are Doing and How Can We Improve? (2016, methodology): “Fourth, the Kaiser criterion is the most popular factor retention method, despite a long history of voiced concerns (Kline, 2014; Patil et al., 2008).”