Effect size and power

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6 Terms

1
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Effect size

Estimates magnitude of effect difference b/w two groups (mean difference)

ex: Coefficients like beta or r

2
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3 types of effect statistics and use

d statistics: Cohen’s d or Hedges’ g

  • response is continuous, predictor is categorical

  • d = how many SD’s two groups differ by

r statistics: Correlation coefficients like Pearson’s

  • both continuous

odds ratio: Comparative risk measurements

  • response: binary, predictor: binary or continuous

3
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what is used to test statistical power (4)

effect size

sample size

significance criterion

power

4
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Effect size formula

difference in means / SD

5
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2 things positive correlated with power

sample size, effect size, alpha

6
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2 power analysis

a priori: Setting up larger experiment

post hoc: How powerful conclusion is