Ratios and effect size

Responding to a related pair of measurements is often expressed as a single discrimination ratio. Authors have used various discrimination ratios; yet, little information exists to guide their choice. A second use of ratios is to correct for the influence of a nuisance variable on the measurement of...

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Main Author: Robinson, Jasper
Format: Article
Published: American Psychological Association 2017
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Online Access:https://eprints.nottingham.ac.uk/42785/
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author Robinson, Jasper
author_facet Robinson, Jasper
author_sort Robinson, Jasper
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description Responding to a related pair of measurements is often expressed as a single discrimination ratio. Authors have used various discrimination ratios; yet, little information exists to guide their choice. A second use of ratios is to correct for the influence of a nuisance variable on the measurement of interest. I examine four discrimination ratios using simulated data sets. Three ratios, of the form a/(a + b), b/(a + b), and (a - b)/(a + b), introduced distortions to their raw data. The fourth ratio, (b - a)/b largely avoided such distortions and was the most sensitive at detecting statistical differences. Effect size statistics were also often improved with a correction ratio. Gustatory sensory preconditioning experiments involved measurement of rats’ sucrose and saline consumption; these flavors served as either a target flavor or a control flavor and were counterbalanced across rats. However, sensory preconditioning was often masked by a bias for sucrose over saline. Sucrose and saline consumption scores were multiplied by the ratio of the overall consumption to the consumption of that flavour alone, which corrected the bias. The general utility of discrimination and correction ratios for data treatment is discussed.
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spelling nottingham-427852020-05-04T19:00:37Z https://eprints.nottingham.ac.uk/42785/ Ratios and effect size Robinson, Jasper Responding to a related pair of measurements is often expressed as a single discrimination ratio. Authors have used various discrimination ratios; yet, little information exists to guide their choice. A second use of ratios is to correct for the influence of a nuisance variable on the measurement of interest. I examine four discrimination ratios using simulated data sets. Three ratios, of the form a/(a + b), b/(a + b), and (a - b)/(a + b), introduced distortions to their raw data. The fourth ratio, (b - a)/b largely avoided such distortions and was the most sensitive at detecting statistical differences. Effect size statistics were also often improved with a correction ratio. Gustatory sensory preconditioning experiments involved measurement of rats’ sucrose and saline consumption; these flavors served as either a target flavor or a control flavor and were counterbalanced across rats. However, sensory preconditioning was often masked by a bias for sucrose over saline. Sucrose and saline consumption scores were multiplied by the ratio of the overall consumption to the consumption of that flavour alone, which corrected the bias. The general utility of discrimination and correction ratios for data treatment is discussed. American Psychological Association 2017-08-14 Article PeerReviewed Robinson, Jasper (2017) Ratios and effect size. Journal of Experimental Psychology . ISSN 0022-1015 effect size discrimination learning discrimination ratio suppression ratio reduction http://psycnet.apa.org/fulltext/2017-34742-001.pdf doi:10.1037/xan0000143 doi:10.1037/xan0000143
spellingShingle effect size
discrimination learning
discrimination ratio
suppression ratio
reduction
Robinson, Jasper
Ratios and effect size
title Ratios and effect size
title_full Ratios and effect size
title_fullStr Ratios and effect size
title_full_unstemmed Ratios and effect size
title_short Ratios and effect size
title_sort ratios and effect size
topic effect size
discrimination learning
discrimination ratio
suppression ratio
reduction
url https://eprints.nottingham.ac.uk/42785/
https://eprints.nottingham.ac.uk/42785/
https://eprints.nottingham.ac.uk/42785/