Skip to main content
SpringerLink
Log in

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

  • Commentary for the Methodology special
  • Published:
International Journal of Clinical Pharmacy Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Nelson EC, Eftimovska E, Lind C, Hager A, Wasson JH, Lindblad S. Patient reported outcome measures in practice. BMJ. 2015;350. doi:10.1136/bmj.g7818.

  2. Martin BA, Chui MA, Thorpe JM, Mott DA, Kreling DH. Development of a scale to measure pharmacists’ self-efficacy in performing medication therapy management services. Res Soc Adm Pharm. 2010;6(2):155–61.

    Article  Google Scholar 

  3. Dahl JR, Hall AM. A scale to measure pharmacy students’ self-efficacy in performing medication therapy management services. Am J Pharm Educ. 2013;77(9):191.

    Article  PubMed  PubMed Central  Google Scholar 

  4. American Educational Research Association APA. National Council on Measurement in Education Standards for educational and psychological testing. Washington: American Psychological Association; 2014.

    Google Scholar 

  5. Dunn TJ, Baguley T, Brunsden V. From alpha to omega: a practical solution to the pervasive problem of internal consistency estimation. Br J Psychol. 2014;105(3):399–412.

    Article  PubMed  Google Scholar 

  6. Gjalt-Jorn Y. Peters. The alpha and the omega of scale reliability and validity: why and how to abandon Cronbach’s alpha and the route towards more comprehensive assessment of scale quality. Eur Health Psychol. 2015;16(2). http://www.ehps.net/ehp/index.php/contents/article/view/ehp.v16.i2.p56. Accessed 8 Apr 2016.

  7. Crutzen R, Peters G-JY. Scale quality: alpha is an inadequate estimate and factor-analytic evidence is needed first of all. Health Psychol Rev. 2015;1–6. doi:10.1080/17437199.2015.1124240.

  8. Pallant JF, Tennant A. An introduction to the Rasch measurement model: an example using the Hospital Anxiety and Depression Scale (HADS). Br J Clin Psychol. 2007;46(1):1–18.

    Article  PubMed  Google Scholar 

  9. van der Eijk C, Rose J. Risky business: factor analysis of survey data—assessing the probability of incorrect dimensionalisation. PLoS One. 2015;10(3):e0118900.

    Article  PubMed  PubMed Central  Google Scholar 

  10. The Canadian Council for Accreditation of Pharmacy Programs. Standards for the first professional degrees in pharmacy programs. 2013. http://www.ccapp-accredit.ca/site/pdfs/university/CCAPP_accred_standards_degree_2014.pdf. Accessed 23 Apr 2015.

  11. Bollen K, Lennox R. Conventional wisdom on measurement: a structural equation perspective. Psychol Bull. 1991;110(2):305–14.

    Article  Google Scholar 

  12. Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Market Res JMR. 1981;18(1):39–50.

    Article  Google Scholar 

  13. Schreiber JB. Core reporting practices in structural equation modeling. Res Soc Adm Pharm. 2008;4(2):83–97.

    Article  Google Scholar 

  14. Fike DS, Zorek JA, MacLaughlin AA, Samiuddin M, Young RB, MacLaughlin EJ. Development and validation of the student perceptions of physician-pharmacist interprofessional clinical education (SPICE) instrument. Am J Pharm Educ. 2013;77(9):190.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Lee C, Segal R, Kimberlin C, Smith WT, Weiler RM. Reliability and validity for the measurement of moral disengagement in pharmacists. Res Soc Adm Pharm. 2013;10(2):297–312.

  16. Campbell DT, Fiske DW. Convergent and discriminant validation by the multitrait–multimethod matrix. Psychol Bull. 1959;56(2):81–105.

    Article  CAS  PubMed  Google Scholar 

  17. Heritage B, Pollock C, Roberts LD. Confirmatory factor analysis of Warr, Cook, and Wall’s (1979) Job Satisfaction Scale. Aust Psychol. 2015;50(2):122–9.

    Article  Google Scholar 

  18. Warr P, Cook J, Wall T. Scales for the measurement of some work attitudes and aspects of psychological well-being. J Occup Psychol. 1979;52(2):129–48.

    Article  Google Scholar 

  19. Sijtsma K. On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika. 2009;74(1):107–20.

    Article  PubMed  Google Scholar 

  20. Dagger TS, Sweeney JC, Johnson LW. A hierarchical model of health service quality: scale development and investigation of an integrated model. J Serv Res. 2007;10(2):123.

    Article  Google Scholar 

  21. Hair J, Black W, Babin B, Anderson R, Tatham R. Multivariate data analysis. Upper Saddle River: Wiley; 2006. ISBN:0130329290.

    Google Scholar 

  22. Raykov T. Scale reliability evaluation with LISREL 8.50. 2003. www.ssicentral.com/lisrel/techdocs/reliabil.pdf. Accessed 16 Oct 2015.

  23. Anderson JC, Gerbing DW. Structural equation modeling in practice: a review and recommended two-step approach. Psychol Bull. 1988;103(3):411–23.

    Article  Google Scholar 

  24. Cizek GJ. Defining and distinguishing validity: interpretations of score meaning and justifications of test use. Psychol Methods. 2012;17(1):31–43.

    Article  PubMed  Google Scholar 

  25. Burnham KP, Anderson DR. Model selection and multimodel inference: a practical information-theoretic approach. New York: Springer; 2002.

    Google Scholar 

Download references

Funding

None.

Conflicts of interest

There are no conflicts of interest in authorship of this article.

Author information

Authors and Affiliations

  1. Faculty of Pharmacy, University of Sydney, Sydney, Australia

    Stephen R. Carter

Authors
  1. Stephen R. Carter
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Stephen R. Carter.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Carter, S.R. Using confirmatory factor analysis to manage discriminant validity issues in social pharmacy research. Int J Clin Pharm 38, 731–737 (2016). https://doi.org/10.1007/s11096-016-0302-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11096-016-0302-9

Keywords

Search

Navigation