Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Likert scales, levels of measurement and the “laws” of statistics

Likert scales, levels of measurement and the “laws” of statistics Reviewers of research reports frequently criticize the choice of statistical methods. While some of these criticisms are well-founded, frequently the use of various parametric methods such as analysis of variance, regression, correlation are faulted because: (a) the sample size is too small, (b) the data may not be normally distributed, or (c) The data are from Likert scales, which are ordinal, so parametric statistics cannot be used. In this paper, I dissect these arguments, and show that many studies, dating back to the 1930s consistently show that parametric statistics are robust with respect to violations of these assumptions. Hence, challenges like those above are unfounded, and parametric methods can be utilized without concern for “getting the wrong answer”. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Advances in Health Sciences Education Springer Journals

Likert scales, levels of measurement and the “laws” of statistics

Norman, Geoff
Advances in Health Sciences Education , Volume 15 (5) – Feb 10, 2010
Download PDF
8 pages

Loading next page...
 
/lp/springer-journals/likert-scales-levels-of-measurement-and-the-laws-of-statistics-8O4ud1zuOu

References (22)

Publisher
Springer Journals
Copyright
Copyright © 2010 by Springer Science+Business Media B.V.
Subject
Education; Medical Education
ISSN
1382-4996
eISSN
1573-1677
DOI
10.1007/s10459-010-9222-y
pmid
20146096
Publisher site
See Article on Publisher Site

Abstract

Reviewers of research reports frequently criticize the choice of statistical methods. While some of these criticisms are well-founded, frequently the use of various parametric methods such as analysis of variance, regression, correlation are faulted because: (a) the sample size is too small, (b) the data may not be normally distributed, or (c) The data are from Likert scales, which are ordinal, so parametric statistics cannot be used. In this paper, I dissect these arguments, and show that many studies, dating back to the 1930s consistently show that parametric statistics are robust with respect to violations of these assumptions. Hence, challenges like those above are unfounded, and parametric methods can be utilized without concern for “getting the wrong answer”.

Journal

Advances in Health Sciences Education – Springer Journals

Published: Feb 10, 2010

There are no references for this article.