Abstract
Correlational analyses are one of the most popular quantitative methods, yet also one of the mostly frequently misused methods in social and behavioral research, especially when analyzing ordinal data from Likert or other rating scales. Although several correlational analysis options have been developed for ordinal data, there seems to be a lack of didactically written literature illustrating the appropriate use and differences among them. The purpose of this paper is to provide a synthesis of correlational analysis options when analyzing ordinal data. These options span from the traditional methods, such as Pearson’s r, to more recent developments, such as Bayesian estimation of polychoric correlations. An illustration of these methods utilizing a contemporary dataset is provided.
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Choi, J., Peters, M. & Mueller, R.O. Correlational analysis of ordinal data: from Pearson’s r to Bayesian polychoric correlation. Asia Pacific Educ. Rev. 11, 459–466 (2010). https://doi.org/10.1007/s12564-010-9096-y
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DOI: https://doi.org/10.1007/s12564-010-9096-y