An Analysis of U-Value as a Measure of Variability.

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Bibliographic Details
Title: An Analysis of U-Value as a Measure of Variability.
Authors: Kong, Xiuyan, McEwan, James, Bizo, Lewis, Foster, T.
Source: Psychological Record. Dec2017, Vol. 67 Issue 4, p581-586. 6p.
Subjects: Differences, Variability (Psychometrics), Probability theory, Regression analysis, Data analysis
Abstract: The variability in behavior has frequently been assessed using a measure known as the U-value. Of concern in this article were the limits and constraints on U-value as a measure of variability. The relation between the U-value and aspects of variability was examined using three sets of simulated data. Our analysis demonstrates that the U-value as a measure of variability on its own fails to capture repetitive patterns in the sequence of responding. The U-value was shown to reflect the evenness of the distributions of responses across the categories/options used; however, when the number of categories actually used by the participant differed from the total number available, the relation between U-values and the number of categories allocated with responses was shown to be nonlinear. It was also shown that the same value of U can represent different levels of evenness in response distributions over categories, depending on the number of categories/options actually used. These constraints and limitations are discussed in relation to how researchers might report on behavioral variability. [ABSTRACT FROM AUTHOR]
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Database: Psychology and Behavioral Sciences Collection
Description
Abstract:The variability in behavior has frequently been assessed using a measure known as the U-value. Of concern in this article were the limits and constraints on U-value as a measure of variability. The relation between the U-value and aspects of variability was examined using three sets of simulated data. Our analysis demonstrates that the U-value as a measure of variability on its own fails to capture repetitive patterns in the sequence of responding. The U-value was shown to reflect the evenness of the distributions of responses across the categories/options used; however, when the number of categories actually used by the participant differed from the total number available, the relation between U-values and the number of categories allocated with responses was shown to be nonlinear. It was also shown that the same value of U can represent different levels of evenness in response distributions over categories, depending on the number of categories/options actually used. These constraints and limitations are discussed in relation to how researchers might report on behavioral variability. [ABSTRACT FROM AUTHOR]
ISSN:00332933
DOI:10.1007/s40732-017-0219-2