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Using confirmatory factor analysis to manage discriminant validity issues in social pharmacy research.

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 particula...

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Published in:International Journal of Clinical Pharmacy Vol. 38; no. 3; pp. 731 - 738
Main Authors: Carter, Stephen, Carter, Stephen R
Format: tables/charts Journal Article
Published: Springer Nature Jun2016
Online Access:View this record in EBSCOhost
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      dt: Jun2016
      vid: 38
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11096-016-0302-9
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        atl: Using confirmatory factor analysis to manage discriminant validity issues in social pharmacy research.
      aug:
        au:
          Carter, Stephen
          Carter, Stephen R
        affil: Faculty of Pharmacy, University of Sydney, Sydney Australia
      sug:
        subj:
          Models, Statistical
          Factor Analysis
          Reproducibility of Results
          Analysis of Variance
      ab: 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.
      pubtype: Academic Journal
      doctype:
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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