1 / 9

Power and Effect Size

Power and Effect Size. D. Wayne Mitchell, Ph.D. Kayla N. Jordan – Statistical Analyst R stats Institute Psychology Department Missouri State University. Review of Statistical Terms I. Type I Error Type II Error Power IV. Effect Size. Four Common Effect Size Indices

felixc
Download Presentation

Power and Effect Size

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Power and Effect Size D. Wayne Mitchell, Ph.D. Kayla N. Jordan – StatisticalAnalyst Rstats Institute Psychology Department Missouri State University

  2. Review of Statistical Terms • I. Type I Error • Type II Error • Power • IV. Effect Size

  3. Four Common Effect Size Indices • (r-squared) r2 • (omega-squared) ω2 • (eta-squared) η2 • Cohen’s d

  4. Size! Small, Medium, Large? Cohen’s d = .20; r 2= .01 (small) Cohen’s d = .50; r 2= .06 (medium) Cohen’s d = .80; r 2= .14 (large)

  5. Given the correlation result: • (r (98) = .40, p < .05); r2 = .16 • Given the t-test result: • (t (22) = 4.16, p < .05) • ω2 = (t2-1)/ (t2 + df +1) = .40 r2 or η2 = t2/ (t2 + df ) = .44 Cohen’s d = 2t / = 1.77

  6. One-Way ANOVA Results: • See Pages 4 and 5 • Omega-Squared • Eta-Squared • Glasses Delta

  7. To do a Power Analysis • See Suggestions; Page 7 • Have to Estimate an Effect Size • Estimate the Smallest Effect that You Want to Detect • Realize the Complexity of the Design Requires Study to do Appropriate Power Analysis

  8. Some Rules of Thumb with Correlation – Regression • N > 50 + 8m (m = # IVs) • N > 50 + m (for individual predictions) • The effect one might expect… • rxy = est. rxy √ rxx ryy

  9. Some Needed Formulas f 2= eta2 / 1 - eta2 d = Mean1 – Mean2 √ s12+ s22 / 2

More Related