title: Using confirmatory factor analysis to manage discriminant validity issues in social pharmacy research.
abstract: Background Confirmatory factory analysis (CFA) and structural equation modelling (SEM) are increasingly used in social pharmacy research. One of the key benefits of CFA is that it allows researchers to provide evidence for the validity of internal factor structure of measurement scales. In particular, CFA can be used to provide evidence for the validity of the assertion that a hypothesized multi-dimensional scale discriminates between sub-scales. Aim This manuscript aims to provide guidance for researchers who wish to use CFA to provide evidence for the internal factor structure of measurement scales. Methods The manuscript places discriminant validity in the context of providing overall validity evidence for measurement scales. Four examples from the recent social pharmacy literature are used to critically examine the various methods which are used to establish discriminant validity. Using a hypothetical scenario, the manuscript demonstrates how commonly used output from CFA computer programs can be used to provide evidence for separateness of sub-scales within a multi-dimensional scale. Conclusion The manuscript concludes with recommendations for the conduct and reporting of studies which use CFA to provide evidence of internal factor structure of measurement scales.
authors.affiliation: Faculty of Pharmacy, University of Sydney, Sydney, Australia. stephen.carter@sydney.edu.au.
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Carter
mesh_terms: D000704:Analysis of Variance; D005163:Factor Analysis, Statistical; D006801:Humans; D015233:Models, Statistical; D000070838:Pharmacy Research / Q000706:statistics & numerical data*; D015203:Reproducibility of Results
keywords: Average variance extracted; Discriminant validity; Structural equation modelling