PPT-Sample size re-assessment

some random observations PSI 2 nd November 2016 Simon Day s imondayCTCTLtdcouk The plan I was an author on one of the very early papers on sample size reestimation Birkett and Day . 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: . Presented by :Dr. . Reshma.S. . Moderator : Dr. . Subodh. S Gupta. Why do we need sample size calculation?. When should we calculate sample size?. Basic principles for sample size calculation. Derivation of sample size formula. Excel. GrowingKnowing.com © 2011. 1. GrowingKnowing.com © 2011. Sample size. How big should a sample be for a valid study?. Why phone 10,000 students if phoning 50 is enough?. Large samples take longer and cost more. Manual. GrowingKnowing.com © 2011. 1. GrowingKnowing.com © 2011. Sample size. How big should a sample be for a valid study?. Why phone 10,000 students if phoning 50 is enough?. Large samples take longer and cost more. 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.. 1. GrowingKnowing.com © 2011. Sample size. How big should a sample be for a valid study?. Why phone 10,000 students if phoning 50 is enough?. Large samples take longer and cost more. What if a sample of 50 is not enough, you need 51 for a valid study?. Q4: After completing the Thinking Globally course I am able to describe differences between cultural perspectives and offer explanations or historical contexts for those differences (indicate level of agreement). . 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. 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. nQuery. Lead Researcher. FDA Guest Speaker. Guest Lecturer. Webinar Host. HOSTED BY: . Ronan Fitzpatrick. Webinar Overview. Adaptive Designs and Sample Size Re-estimation (SSR). Blinded Sample Size Re-estimation . 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. Correlation, Agreement, and Diagnostic Measures. Denis Desmond. Research Statistician. nQuery. Webinar. Host. Agenda. Correlation Methods and Sample Size. Agreement Methods and Sample Size. Diagnostic Testing Methods and 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.