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Effect Size

Effect Size. Effect sizes provides a measure of the clinical importance of an empirical finding There are many types of effect size. Cohen’s D. Cohen’s d is a measure of effect size that scales mean differences in standard deviation units Classifications for Cohen’s d

ariel-meyers
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Effect Size

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  1. Effect Size • Effect sizes provides a measure of the clinical importance of an empirical finding • There are many types of effect size

  2. Cohen’s D • Cohen’s d is a measure of effect size that scales mean differences in standard deviation units • Classifications for Cohen’s d • Small effect = 0.2 standard deviation • Medium effect = 0.5 standard deviation • Large effect = 0.8 standard deviation

  3. r • r measures the proportion of variance that the IV accounts for in the dv • Classification for r • Small effect = less than .25 • Medium effect = .25 to .40 • Large effect = .40 or more

  4. η (Eta) • η (eta) is a measure of effect size for ANOVA • It measures the proportion of total variance that is accounted for by group differences • Classifications for η • Small effect = less than .25 • Medium effect = .25 to .40 • Large effect = .40 or more

  5. Effect Size for Goodness of Fit • r is used to measure effects for a goodness of fit test • Classifications for r • Small effect = less than .30 • Medium effect = .30 to .50 • Large effect = more than .50

  6. Effect Size for Test of Independence • φ (phi) is used to measure effect size for a test of independence • Classifications of φ • Small effect = less than .30 • Medium effect = .30 to .50 • Large effect = more than .50

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