Survey research and design in psychology/Lectures/Power & effect sizes

Outline
Explains use of, and issues involved in:
 * 1) significance testing
 * 2) inferential decision making
 * 3) statistical power
 * 4) effect sizes
 * 5) confidence intervals
 * 6) publication bias
 * 7) academic integrity

Conclusions

 * Decide on H0 and H1 (1 or 2 tailed)
 * Calculate power beforehand and adjust the design to detect a minimum effect size (ES)
 * Report statistical power, statistical significance, ES, confidence interval
 * Compare results with meta-analyses and/or meaningful benchmarks
 * Take a balanced, critical approach, striving for objectivity and academic integrity

Readings

 * 1) Howitt and Cramer (2014a):
 * 2) Chapter 35: The size of effects in statistical analysis: Do my findings matter? (pp. 487-494)
 * 3) Chapter 36: Meta-analysis: Combining and exploring statistical findings from previous research (pp. 495-514)
 * 4) Chapter 38: Confidence intervals (pp. 529-539)
 * 5) Chapter 40: Statistical power: Getting the sample size right (pp. 562-586)
 * 6) Wilkinson, L., & APA Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594-604.

Handout

 * Lecture slides (Google Slides)


 * 2018:
 * [[Media:SRDP Lecture09Handout PES 6slidesperpage.pdf|Download 6 slides to a page]]: SRDP Lecture09Handout PES 6slidesperpage.pdf
 * [[Media:SRDP Lecture09Handout PES 3slidesperpage.pdf|Download 3 slides to a page]]: SRDP Lecture09Handout PES 3slidesperpage.pdf