title: Reporting practices in confirmatory factor analysis: an overview and some recommendations.
abstract: Reporting practices in 194 confirmatory factor analysis studies (1,409 factor models) published in American Psychological Association journals from 1998 to 2006 were reviewed and compared with established reporting guidelines. Three research questions were addressed: (a) how do actual reporting practices compare with published guidelines? (b) how do researchers report model fit in light of divergent perspectives on the use of ancillary fit indices (e.g., L.-T. Hu & P. M. Bentler, 1999; H. W. Marsh, K.-T., Hau, & Z. Wen, 2004)? and (c) are fit measures that support hypothesized models reported more often than fit measures that are less favorable? Results indicate some positive findings with respect to reporting practices including proposing multiple models a priori and near universal reporting of the chi-square significance test. However, many deficiencies were found such as lack of information regarding missing data and assessment of normality. Additionally, the authors found increases in reported values of some incremental fit statistics and no statistically significant evidence that researchers selectively report measures of fit that support their preferred model. Recommendations for reporting are summarized and a checklist is provided to help editors, reviewers, and authors improve reporting practices.
authors.affiliation: Department of Psychology, University of Windsor, Ontario, Canada. djackson@uwindsor.ca
authors.forename: Dennis L
authors.initials: DL
authors.lastname: Jackson
authors.forename: J Arthur
authors.initials: JA
authors.lastname: Gillaspy
authors.forename: Rebecca
authors.initials: R
authors.lastname: Purc-Stephenson
mesh_terms: D005163:Factor Analysis, Statistical; D019983:Guideline Adherence; D006801:Humans; D008432:Mathematical Computing; D015233:Models, Statistical; D010506:Periodicals as Topic; D011584:Psychology / Q000592:standards*; D011643:Publishing; D015203:Reproducibility of Results; D012106:Research / Q000706:statistics & numerical data*; D012107:Research Design / Q000706:statistics & numerical data*; D012984:Software