The Effect of the Number of Observations per Parameter in Misspecified Confirmatory Factor Analytic Models

By Dennis L. Jackson. 2007

75 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/dec136fcac293f656acb5bab8a3dacc5945503f3

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In Computer Networks and Communications

In Information Systems and Management

In Management Science and Operations Research

Citations in the corpus

A Validation Study of the Resilience Scale for Adolescents (READ) (2010, background): “(2006) study (see Jackson 2007).”
A Note on Sample Size and Solution Propriety for Confirmatory Factor Analytic Models (2013, background): “…endorsed to varying degrees (Bollen, 1989; Herzog & Boomsma, 2009; Kim & Bentler, 2006; Kline, 2005; Marsh et al., 1988; Mueller, 1996; Nevitt & Hancock, 2004; Ullman, 1996); however, recommendations based on n/q have also been questioned (Jackson, 2003, 2007; Marsh, Hau, Balla, & Grayson, 1998).”
Reporting practices in confirmatory factor analysis: an overview and some recommendations. (2009, background): “Drawing from previous studies (Fan et al., 1999; Hu & Bentler, 1998, 1999; Jackson, 2007; Marsh, Balla, & Hau, 1996; Marsh, Hau, Balla, & Grayson, 1998), the following fit measures tend to perform well with respect to detecting model misspecification and lack of dependence on sample size: gamma hat…”
Item Parceling in Structural Equation Modeling: A Primer (2008, result): “A recent simulation study suggested that the impact of the sample size per parameter ratio is small relative to other conditions such as sample size per se (Jackson, 2007) and the model quality (Gagné & Hancock, 2006).”
Small-Sample Robust Estimators of Noncentrality-Based and Incremental Model Fit (2009, unknown): “As mentioned earlier, however, although rules of thumb, like N:t ratios, might provide sensible guidelines for applied researchers in many situations, they should always be employed with abundant vigilance and leniency (e.g., Brown, 2006; Jackson, 2001, 2003, 2007).”
The Model Size Effect in SEM: Inflated Goodness-of-Fit Statistics Are Due to the Size of the Covariance Matrix (2012, background): “…of approximation (RMSEA) are based on the TML statistic and, consequently, might also produce misleading results under these conditions (Chen, Curran, Bollen, Kirby, & Paxton, 2008; Curran et al., 2002; Ding, Velicer, & Harlow, 1995; Herzog & Boomsma, 2009; Jackson, 2007; Kenny & McCoach, 2003).”
Current Methodological Considerations in Exploratory and Confirmatory Factor Analysis (2011, background): “…numerous rules-of-thumb recommendations of appropriate sample sizes based on sample size relative to the number of parameters being estimated (e.g., Jackson, 2007), the number of variables per factor (e.g., Marsh et al., 1998), and so on, but the limitation of these recommendations is the model(s)…”