PPT-Power and Sample Size: Why Should We Care?

November 17 2015 Allen Kunselman MA Division of Biostatistics and Bioinformatics Department of Public H ealth Sciences Quotes An approximate answer to the right question is worth a good deal more than an exact answer to the wrong question. brPage 1br Sample brPage 2br Sample brPage 3br Sample brPage 4br Sample brPage 5br Sample brPage 6br Sample brPage 7br Sample brPage 8br Sample x x x x Study Design and Sample Size. Ideally we are involved in a study from the beginning. As statisticians (an epidemiologist) part of our role is to ensure the study is designed to address the primary hypothesis under consideration. 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: . 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. Chapter 8. Hyde, Fennema & Lamon (1990). Mean gender differences in mathematical reasoning were very small.. When extreme tails of the distributions were removed, differences were smaller and reversed direction (favored girls). When I cover the entire population I get to know the truth – precisely.. That means that when my sample size is high I get a more precise answer.. That means that when my sample size increases my preciseness increases. +. Principles of Simulation. Benjamin Neale. March 4. th. , 2010 . International Twin Workshop, Boulder, CO. Slide of Questions. What is power?. What affects power?. How do we calculate power?. What is simulation?. Review of Type I & Type II Errors. When we conduct a test of any hypothesis regardless of the test used we make one of two possible decisions:. Reject the null (H. o. ) in favor of the alternative (H. Office of Methodological & Data Sciences. November . 13, 2015. Sarah Schwartz. www.cehs.usu.edu/research/omds. Quantitative Research. Research Question. Clear, focused & concise question that drives the study. 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. Design and Endpoint Considerations. Demonstrated on . Head of Statistics. nQuery. Lead Researcher. FDA Guest Speaker. Guest Lecturer. Webinar Host. HOSTED BY: . Ronan Fitzpatrick. AGENDA. Introduction to Non-inferiority Testing. Plan. Review of hypothesis testing. Power and sample size . Basic concepts. Formulae for common study designs. Using the software. When should you think about power & sample size?. Start thinking about statistics when you are planning your study. Binary, Ordinal and . Contingency Table Data. Ronan Fitzpatrick. Lead Statistician. nQuery. Webinar. Host. Agenda. Categorical Data Overview. Binary Data Methods & Sample Size. Ordinal Data Methods & Sample Size. By: Harrison . Reeder. Mentor: Dr. Kathryn . Chaloner. Iowa Summer Institute in Biostatistics. Outline. What exactly does that title mean?. Basic Clinical Trial design. Interim Monitoring for Efficacy.