One-Way BG ANOVA

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# One-Way BG ANOVA - PowerPoint PPT Presentation

One-Way BG ANOVA. Andrew Ainsworth Psy 420 Obtained from www.csun.edu/~ata20315/psy420/One-Way\%20BG\%20 ANOVA .ppt. Effect Size. A significant effect depends: Size of the mean differences (effect) Size of the error variance Degrees of freedom Practical Significance

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### One-Way BG ANOVA

Andrew Ainsworth

Psy 420

Obtained from

www.csun.edu/~ata20315/psy420/One-Way%20BG%20ANOVA.ppt

Effect Size
• A significant effect depends:
• Size of the mean differences (effect)
• Size of the error variance
• Degrees of freedom
• Practical Significance
• Is the effect useful? Meaningful?
• Does the effect have any real utility?
Effect Size
• Raw Effect size –
• Just looking at the raw difference between the groups
• Can be illustrated as the largest group difference or smallest (depending)
• Can’t be compared across samples or experiments
Effect Size
• Standardized Effect Size
• Expresses raw mean differences in standard deviation units
• Usually referred to as Cohen’s d
Effect Size
• Standardized Effect Size
• Cohen established effect size categories
• .2 = small effect
• .5 = moderate effect
• .8 = large effect
Effect Size
• Percent of Overlap
• There are many effect size measures that indicate the amount of total variance that is accounted for by the effect
Effect Size
• Percent of Overlap
• Eta Squared
• simply a descriptive statistic
• Often overestimates the degree of overlap in the population
Effect Size
• Omega Squared
• This is a better estimate of the percent of overlap in the population
• Corrects for the size of error and the number of groups
Our Example EPRS8540
• Eta Squared
• Small .01
• Medium .06
• Large .14

Cohen (1977)

• Omega Squared
• Small < .06
• Medium .06 - .15
• Large > .15

Cohen (1977)

Our Example EPRS8540
• There was no significant price difference among the three store types (F2, 9 = 3.12, P > .05, ).
References
• Cohen, J. (1977). Statistical power analysis for the behavioral sciences. NY: Academic Press. Cited with regard to intepretation of omega-square.
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences . Second ed., Hillsdale, NJ: Erlbaum.
• Olejnik, S., & Algina, J. (2003). Generalized eta and omega statistics: Measured for effect size for some common research designs, Psychological Methods, 8, 434 – 447.