IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v51y2017i5d10.1007_s11135-016-0378-2.html
   My bibliography  Save this article

A recommendation for applied researchers to substantiate the claim that ordinal variables are the product of underlying bivariate normal distributions

Author

Listed:
  • Jarl K. Kampen

    (Wageningen University)

  • Arie Weeren

    (Antwerp University)

Abstract

A simulation study was carried out to study the behaviour of the polychoric correlation coefficient in data not compliant with the assumption of underlying continuous variables. Such data can produce relatively high estimated polychoric correlations (in the order of .62). Applied researchers are prone to accept these artefacts as input for elaborate modelling (e.g., structural equation models) and inferences about reality justified by sheer magnitude of the correlations. In order to prevent this questionable research practice, it is recommended that in applications of the polychoric correlation coefficient, data is tested with goodness-of-fit of the BND, that such statistic is reported in published applications, and that the polychoric correlation is not applied when the test is significant.

Suggested Citation

  • Jarl K. Kampen & Arie Weeren, 2017. "A recommendation for applied researchers to substantiate the claim that ordinal variables are the product of underlying bivariate normal distributions," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2163-2170, September.
  • Handle: RePEc:spr:qualqt:v:51:y:2017:i:5:d:10.1007_s11135-016-0378-2
    DOI: 10.1007/s11135-016-0378-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-016-0378-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11135-016-0378-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. McKEE J. McCLENDON, 1991. "Acquiescence and Recency Response-Order Effects in Interview Surveys," Sociological Methods & Research, , vol. 20(1), pages 60-103, August.
    2. Jaehwa Choi & Sunhee Kim & Jinsong Chen & Sharon Dannels, 2011. "A Comparison of Maximum Likelihood and Bayesian Estimation for Polychoric Correlation Using Monte Carlo Simulation," Journal of Educational and Behavioral Statistics, , vol. 36(4), pages 523-549, August.
    3. Jarl Kampen & Marc Swyngedouw, 2000. "The Ordinal Controversy Revisited," Quality & Quantity: International Journal of Methodology, Springer, vol. 34(1), pages 87-102, February.
    4. Robert O'Brien & Pamela Homer, 1987. "Corrections for coarsely categorized measures: LISREL's polyserial and polychoric correlations," Quality & Quantity: International Journal of Methodology, Springer, vol. 21(4), pages 349-360, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Coltman, Tim & Devinney, Timothy M. & Keating, Byron W., 2010. "Best-worst scaling approach to predict customer choice for 3PL services," MPRA Paper 40492, University Library of Munich, Germany.
    2. Hadžibajramovic, Emina & Svensson, Elisabeth & Ahlborg Jr, Gunnar, 2013. "Construction of a global score from multi-item questionnaires in epidemiological studies," Working Papers 2013:4, Örebro University, School of Business.
    3. Manuel Carlos Vallejo-Martos, 2016. "Institutionalism and the Influence of the Cultural Values of the Family Subsystem on the Management of the Small–Medium Family Firms," Systems Research and Behavioral Science, Wiley Blackwell, vol. 33(1), pages 119-137, January.
    4. Weijters, Bert & Cabooter, Elke & Schillewaert, Niels, 2010. "The effect of rating scale format on response styles: The number of response categories and response category labels," International Journal of Research in Marketing, Elsevier, vol. 27(3), pages 236-247.
    5. Katrin Auspurg & Annette Jäckle, 2017. "First Equals Most Important? Order Effects in Vignette-Based Measurement," Sociological Methods & Research, , vol. 46(3), pages 490-539, August.
    6. Michele Lalla, 2017. "Fundamental characteristics and statistical analysis of ordinal variables: a review," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(1), pages 435-458, January.
    7. Giancarlo MANZI & Pier Alda FERRARI, "undated". "Statistical methods for evaluating satisfaction with public services Abstract: Contrary to private enterprises, public enterprises can be unaware of the impact of their performance when providing serv," CIRIEC Working Papers 1404, CIRIEC - Université de Liège.
    8. Florian Schuberth & Jörg Henseler & Theo K. Dijkstra, 2018. "Partial least squares path modeling using ordinal categorical indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 9-35, January.
    9. Alessandro Barbiero & Asmerilda Hitaj, 2020. "Goodman and Kruskal’s Gamma Coefficient for Ordinalized Bivariate Normal Distributions," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 905-925, December.
    10. Cabooter, Elke & Weijters, Bert & Geuens, Maggie & Vermeir, Iris, 2016. "Scale format effects on response option interpretation and use," Journal of Business Research, Elsevier, vol. 69(7), pages 2574-2584.
    11. Francisco Holgado–Tello & Salvador Chacón–Moscoso & Isabel Barbero–García & Enrique Vila–Abad, 2010. "Polychoric versus Pearson correlations in exploratory and confirmatory factor analysis of ordinal variables," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(1), pages 153-166, January.
    12. Dolnicar, Sara & Grün, Bettina & Leisch, Friedrich, 2016. "Increasing sample size compensates for data problems in segmentation studies," Journal of Business Research, Elsevier, vol. 69(2), pages 992-999.
    13. Jarl Kampen, 2007. "The Impact of Survey Methodology and Context on Central Tendency, Nonresponse and Associations of Subjective Indicators of Government Performance," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(6), pages 793-813, December.
    14. Kamal, Mustafa & Blacklow, Paul, 2021. "Attitudes to gender and personality in the Australian gender wage gap," Working Papers 2021-07, University of Tasmania, Tasmanian School of Business and Economics.
    15. Pearce, Antony & Pons, Dirk, 2019. "Advancing lean management: The missing quantitative approach," Operations Research Perspectives, Elsevier, vol. 6(C).
    16. Pal, Abhipsa & Herath, Tejaswini & De', Rahul & Raghav Rao, H., 2021. "Why do people use mobile payment technologies and why would they continue? An examination and implications from India," Research Policy, Elsevier, vol. 50(6).
    17. Fredrik Ødegaard & Pontus Roos, 2013. "Measuring Worksite Health Promotion Programs: an application of Structural Equation Modeling with ordinal data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(4), pages 639-653, August.
    18. Giulio D’Epifanio, 2009. "Implicit Social Scaling from an Institutional Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 94(2), pages 203-212, November.
    19. MacKenzie, Scott B. & Podsakoff, Philip M., 2012. "Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies," Journal of Retailing, Elsevier, vol. 88(4), pages 542-555.
    20. Antony Pearce & Dirk Pons & Thomas Neitzert, 2023. "Understanding Lean—Statistical Analysis of Perceptions and Self-Deception Regarding Lean Management," SN Operations Research Forum, Springer, vol. 4(2), pages 1-43, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:qualqt:v:51:y:2017:i:5:d:10.1007_s11135-016-0378-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.