Measuring an effect size from dichotomized data : contrasted results whether using a correlation or an odds-ratio

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Version: author
Serval ID
serval:BIB_36A5FCA0180E
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Measuring an effect size from dichotomized data : contrasted results whether using a correlation or an odds-ratio
Journal
Journal of Educational and Behavioral Statistics
Author(s)
Rousson Valentin
ISSN
1076-9986
Publication state
Published
Issued date
2014
Peer-reviewed
Oui
Volume
39
Number
2
Pages
144-163
Language
english
Abstract
It is well known that dichotomizing continuous data has the effect to decrease statistical power when the goal is to test for a statistical association between two variables. Modern researchers however are focusing not only on statistical significance but also on an estimation of the "effect size" (i.e., the strength of association between the variables) to judge whether a significant association is also clinically relevant. In this article, we are interested in the consequences of dichotomizing continuous data on the value of an effect size in some classical settings. It turns out that the conclusions will not be the same whether using a correlation or an odds ratio to summarize the strength of association between the variables: Whereas the value of a correlation is typically decreased by a factor pi/2 after each dichotomization, the value of an odds ratio is at the same time raised to the power 2. From a descriptive statistical point of view, it is thus not clear whether dichotomizing continuous data leads to a decrease or to an increase in the effect size, as illustrated using a data set to investigate the relationship between motor and intellectual functions in children and adolescents
Keywords
binary data, correlation, continuous data, statistical power, odds ratio, dichotomization
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Create date
24/06/2014 12:32
Last modification date
20/08/2019 13:24
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