<p>Those who have thought at all deeply about measurement mostly agree that some qualitative form of ordering characteristic of an empirical attribute is a precursor to measurement. The thesis of this book, as well as of Cliff's (1996) Ordinal Methods for Behavioral Data Analysis, is that, for the most part, order has to be sufficient for psychology. Often it is all that we have. When so, psychologists, and other social scientists, should recognize the fact and live with it when analyzing data. The authors cite standard test theory as a major, if highly lucrative, sinner in this regard: “the recent emphasis in psychometrics has been too heavily toward the fitting process, to the neglect of the evaluation of appropriateness, except on narrow and nearly irrelevant statistical grounds” (p. 35). The authors say, and I agree, that the pretense that measures of intelligence or other abilities of individuals are normally distributed in certain populations is just that, a pretense. Were it correct, then some count of correct responses should be nonlinearly transformed in order to achieve that norm, leading therefore to interval scale measures for which many standard statistical methods based on the normal distribution are justified. But with
Ordinal Attributes, Ordinal Analyses Only
Abstract
<p>Those who have thought at all deeply about measurement mostly agree that some qualitative form of ordering characteristic of an empirical attribute is a precursor to measurement. The thesis of this book, as well as of Cliff's (1996) Ordinal Methods for Behavioral Data Analysis, is that, for the most part, order has to be sufficient for psychology. Often it is all that we have. When so, psychologists, and other social scientists, should recognize the fact and live with it when analyzing data. The authors cite standard test theory as a major, if highly lucrative, sinner in this regard: “the recent emphasis in psychometrics has been too heavily toward the fitting process, to the neglect of the evaluation of appropriateness, except on narrow and nearly irrelevant statistical grounds” (p. 35). The authors say, and I agree, that the pretense that measures of intelligence or other abilities of individuals are normally distributed in certain populations is just that, a pretense. Were it correct, then some count of correct responses should be nonlinearly transformed in order to achieve that norm, leading therefore to interval scale measures for which many standard statistical methods based on the normal distribution are justified. But withPreview Only. This article cannot be rented because we do not currently have permission from the publisher.
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Ordinal Attributes, Ordinal Analyses Only
Luce, R. Duncan
Follow Contemporary Psychology
, Volume 49 (6): 783
PsycCRITIQUES® – Dec 1, 2004
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