PPT-Effect Size & Power Analysis G*Power

Office of Methodological amp Data Sciences November 13 2015 Sarah Schwartz wwwcehsusueduresearchomds Quantitative Research Research Question Clear focused amp concise question that drives the study. Jed Friedman, World . Bank. SIEF Regional Impact Evaluation Workshop. Beijing, China. July 2009. Adapted from slides by Esther . Duflo. , J-PAL. Planning Sample Size for . Randomized Evaluations. General question: . Size. Robert Coe . @. ProfCoe. ResearchED. . 2013, Dulwich College, 7 Sept 2013. 2. The case for using effect size. What . is Effect Size? . The case for using effect size . (5 reasons). Problems in using effect size . PSY505. Spring term, 2012. April . 11, . 2012. Today’s Class. Power Analysis. Statistical Power. Power Analysis. A set of methods for determining. The probability that you will obtain a statistically significant result, assuming a true effect size and sample size of a certain magnitude. Effect Size & Statistical Power. 1. 1. Effect Size. How “meaningful” is the significant difference?. 1. KNR 445. Statistics. Effect sizes. Slide . 3. Significance vs. meaningfulness. As sample size increases, likelihood of significant difference increases. Cyrus Samii. New York University. ieGovern. Impact Evaluation Workshop. Istanbul, Turkey. January 27-30, 2015. : #. ieGovern. Definition. The . power. of your study measures the . confidence. you can have that it will lead you to dra. ESSM 689. 2015. Meta-analysis. “If . only we knew what we . know…”. -Caria O’ Dell . and Jack Grayson. “. A. nything . you can do, I can . do meta“. “Meta-Analysis. , . Shmeta. -Analysis. Roger E. Kirk. Department of Psychology & Neuroscience. Baylor University. . Three Categories of Measures of . Effect Magnitude. 1. Measures of effect size (typically, standardized mean differences). Dr . John Hattie’s Research. Who is John Hattie?. Professor . and Director of the Melbourne . Educational . Research Institute . C. arried out the . world’s largest evidence-based study . to find out what are the factors that . Cal State Northridge. . 320. Andrew Ainsworth PhD. 2. Major Points. Review. What is power?. What controls power?. Effect size. Power for one sample . t. Power for related-samples. t. Power for two sample . General Sampling Issues. Thinking of the steps in sampling (from theoretical population to respondents)—what are some biases that can come in at each point?. What is the proximity similarity model? What are issues with that model?. Hao. . Zhou & David . Dueber. February 6, 2017. Applied Psychometric Strategies Lab. Applied Quantitative and Psychometric Series. Outline. Fake real life research scenario. Significance testing and statistical errors. Objective. Understand the philosophy of meta-analysis and its contribution to epidemiology and science.. Understand the limitations of meta-analysis. Introduction. Systematic quantitative integration of results . PEP507: Research MethodsEffect Size and Statistical Power Prior to conducting the study (apriori), researchers should;estimate the size of a mean difference that is meaningfulidentify a type II error Presented by Christine R. Wells, Ph.D.. Statistical Methods and Data Analytics. UCLA Office of Advanced Research Computing. What to expect from this workshop. Definition of systematic review and meta-analysis.