The Quality of Factor Solutions in Exploratory Factor Analysis: The Influence of Sample Size, Communality, and Overdetermination

By Kristine Y. Hogarty, Constance V. Hines, Jeffrey D. Kromrey, J. Ferron, Karen R. Mumford. 2005

565 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/73a9225066fb4b7daf98f78999802aa1de792e70

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In Computer Networks and Communications

In Management Science and Operations Research

Citations in the corpus

Practical Considerations for Using Exploratory Factor Analysis in Educational Research. (2013, background): “A strong solution, made up of stable factors, reduces the influence of the sample size; however, a larger sample size decreases sampling error resulting in more stable solutions (Hogarty et al., 2005).”
New Confidence Intervals and Bias Comparisons Show That Maximum Likelihood Can Beat Multiple Imputation in Small Samples (2013, background): “In factor analysis, smaller samples can be adequate if the model is simple and the communalities are high (Hogarty et al., 2005; MacCallum et al., 1999).”
Sample size planning for statistical power and accuracy in parameter estimation. (2008, background): “MacCallum et al. (1999, 2001), Hogarty et al. (2005), Nasser & Wisenbaker (2001), and Velicer & Fava (1998) each review the existing literature and show that, in general, such rules of thumb regarding necessary sample size are oversimplified and should not be trusted.”
Factors impacting teachers' argumentation instruction in their science classrooms (2016, background): “Orthogonal rotations keep the constructs distinct from each other, which can improve the quality of factor solutions for small sample sizes (Hogarty et al., 2005).”
Pixels vs. Paper: Comparing Online and Traditional Survey Methods in Sport Psychology (2006, background): “However, more recent research ( Hogarty, Hines, Kromrey, Ferron, & Mumford, 2005; MacCallum, Widaman, Zhang, & Hong, 1999) suggests that when the number of factors is low (e.g., ≤3), the number of items per factor is high (e.g., ≥4), and factor loadings are high (e.g., ≥.6), CFA using Maximum Likel”
Supervisor Humor and Employee Outcomes: The Role of Social Distance and Affective Trust in Supervisor (2015, unknown): “We used three-item parcels for measures with more than three items to achieve a better variable-to-sample size ratio (our ratio is 6.2, which is relatively low, refer to Hair et al. 1995; Hogarty et al. 2005; Nunnally 1978).”