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

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  • 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
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    References listed on IDEAS

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    3. 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.
    4. Jarl Kampen & Marc Swyngedouw, 2000. "The Ordinal Controversy Revisited," Quality & Quantity: International Journal of Methodology, Springer, vol. 34(1), pages 87-102, February.
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