It seems to fall somewhere in between ordinal and interval scaling. It is somewhat debatable that Likert scaling is ordinal according to Stevens four levels of measurement (nominal, ordinal, interval, or ratio). However the the ordinal data generated by the arithmetic operations involved in the calculation of means require interval level measurements.ĭata obtained from Likert scales can be analysed by nonparametric methods such as Mann-Whitney-Wilcoxon test, and Kruskal-Wallis one-way analysis of variance. In practice, data obtained from Likert scales is analyised using Parametric methods such as Student's t-test or ANOVA are also often used to analyse Likert scale data. The summated test scores, can be worked with anyway way you like. Often items, are analysed by looking at their ability to discriminate between high and low scorers on the test.
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Additionally scales may be analysed by factor analysis, or Guttman/Mokken criteria. The scale and items itself is analysed using "item analysis" methods such a Cronbach's alpha etc. I moved this out of the main body because it's not directly relevant as is. Nonetheless, this is not to say it is not possible to achieve such things with sufficient skill and thought. There ends up being a lot of overlap between categories on the latent continuum and relevant thresholds do not discriminate. I don't use Likert data much for various reasons, but in my experience, when appling Rasch models I have not found that more than 4 or 5 categories contribute additional information. The problem is separating the semantic space so that the categories carry substantive differences, in terms of the attitude, affective disposition, or whatever is relevant to the item statement. evidence within the structure of the data when subjected to analyses that are sensitivie to this. On comment above, I'd like to see evidence for greater granularity with seven categories: i.e. Klonimus 09:31, 23 October 2005 (UTC) Like your comments below, important points for this article. More than 9 categories tends to create a cognitive overload.
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This is because a 5 point scale only allows two for levels of agreement or disagreement. Stephenhumphry 05:17, 15 September 2005 (UTC) Seven or nine point scales tend to give much more granularity.
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Choice is subjective, yes, but that doesn't mean preferences, attitudes, etc. For my part, though, I thank you for the comments, very useful. It's not so much a matter of 'how hot do you want your porridge' - rather, how fine-grained can you make the information without it being artificially so? See polytomous Rasch model for further explanation of this point. The number of categories that can be sustained is an empirical question. Understanding the subjectivity of this survey technique might help readers understand it in their context. It comes down to a Goldilocks problem, how hot do you want your porridge. 7 or 10 choices offer greater granularity, but can be too focused for some surveys. Working in Human-Computer Interactions for web usability, business people often ask, "Why do you use a 1-5 scale and not a 1-10 scale?" I explain that choice is largely subjective. 19 The Website User Survey Picture contains a Glaring Bad Practice.