Using ordinal logistic regression to analyse self-reported usage of, and attitudes towards swearwords

Likert-type data is commonly used in many research fields in humanities: from gaging the usability of different user-interface designs, to determining users’ likeliness to vote for a particular political party, to evaluation of course materials–to name but a few examples. Despite its prevalence, there is still some disagreement within the statistics community on whether Likert-type scales are true ordinal variables, and by implication whether parametric tests are legitimate to be used in such cases (Endresen &Janda 2017).In this paper, we explore one parametric statistical test, viz. cumulative odds ordinal logistic regression (OLR),as an analysis method for self-reported data in the humanities. For illustration purposes, our focus is specifically on data of users’ self-reported usage of, and attitudes towards swearwords, with the aim of identifying demographic attributes that are predictive of their usage and/or attitudes. After a brief description of the data we’re using, including how the data is being collected, we give a layman’s overview of OLR. Since one of our aims is to demonstrate the usability of OLR, we apply our discussion practically to a step-by-step procedure (based on Laerd Statistics 2015) that could be followed easily. We demonstrate the usefulness of the results in reporting on the usage of, and attitude towards two near synonymous Afrikaans swearwords. We show, amongst others, that the odds ratios that are generated as part of the modelling procedure can be used to draw direct conclusions about specific demographic groups.