Is the Selection of Statistical Methods Governed by Level of Measurement?

The notion that nonparametric methods are required as a replacement of parametric statistical methods when the scale of measurement in a research study does not achieve a certain level was discussed in light of recent developments in representational measurement theory. A new approach to examining t...

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Bibliographic Details
Published inCanadian psychology = Psychologie canadienne Vol. 34; no. 4; pp. 390 - 400
Main Authors ZUMBO, BRUNO D, ZIMMERMAN, DONALD W
Format Journal Article
LanguageEnglish
Published Ottawa Canadian Psychological Association 01.10.1993
Educational Publishing Foundation
Subjects
Behavioural sciences
Computer Simulation
Design of experiments
Human
Methodology
Methods
Selection
Social sciences
Statistical analysis
Statistical Tests
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Summary:The notion that nonparametric methods are required as a replacement of parametric statistical methods when the scale of measurement in a research study does not achieve a certain level was discussed in light of recent developments in representational measurement theory. A new approach to examining the problem via computer simulation was introduced. Some of the beliefs that have been widely held by psychologists for several decades were examined by means of a computer simulation study that mimicked measurement of an underlying empirical structure and performed two-sample Student t -tests on the resulting sample data. It was concluded that there is no need to replace parametric statistical tests by nonparametric methods when the scale of measurement is ordinal and not interval.
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ISSN:0708-5591
1878-7304
DOI:10.1037/h0078865