Overview
Want to know how to find the right sample size for your study? Too few subjects and you’ll waste time. Too many subjects and you’ll waste time and money! Learning the concepts of statistical power analysis and how to put the power analysis techniques to use will help to assure that you’ll collect a large enough sample to see significance in the effect you test.
Please join Elaine Eisenbeisz, Owner and Principal of Omega Statistics, as she presents an exploration of power analysis and techniques for determining sample size (a priori techniques). Elaine will take some time during the event to work examples in the free to use G*Power software. She will also present some code and demonstrations for powering studies and performing power analysis simulations in R software.
Webinar Includes : All the training handouts , certificate ,Q/A and 90 mins Live Webinar
Why Should You Attend
The power of your study is the probability that you will find a statistically significant difference or relationship (an “effect”) if that difference or relationship (effect) truly exists in the population.
A study with too small of a sample size is under-powered. This means that even if the effect you are testing for truly exists, you won’t achieve statistical significance. You will waste time by collecting a sample that is too small to properly power a study. Why perform a research if you can’t see significance for your desired effect?
A study with too large of a sample is over-powered. This means that you’ve collected such a large sample that you will see significance even on very small effects. However, the costs of subject recruitment, data collection, and follow-up (if needed) are quite large. Recruiting more subjects than needed unnecessarily inflates the temporal and monetary costs.
Questions related to the feasibility of a study can be answered by power analysis:
- How large of a sample will I need to collect in order to see a significant effect?
- How many subjects will I need if I test an effect that is a bit larger? a bit smaller?
Answers to questions like these will give you an idea if your study is indeed “do-able.”
Key Learning Objectives
- Understanding of a priori power analysis for sample size
- Learn how to calculate sample sizes using open source software
- Overview of power analysis theory and concepts
- Effect size definitions and considerations
- Simulation and study power
- Know what you need to compute sample sizes
Webinar Takeaway
- The usefulness of power analysis
- Overview of power analysis theory and concepts
- Effect size
- Examples of sample size calculations using G*Power software
- Examples of sample size calculations using simulation
- Q&A Session
Who Will Benefit
- Trial Sponsors
- Physicians
- Clinical Investigator
- Clinical Research Associates
- Clinical Project Managers/Leaders
- Regulatory Professionals who use statistical concepts/terminology in reporting
- Medical Writers who need to interpret statistical reports
- IRB review board members
- DSMB members
Elaine Eisenbeisz
Statistician ( 30 + yrs exp.)
Owner & Principal of Omega Statistics
Murrieta, California, United States
Elaine Eisenbeisz is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California. Elaine has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations, to start-up companies and individual researchers.
In addition to her technical expertise, Elaine possesses a talent for conveying statistical concepts and results in a way that people can intuitively understand.
Our Participants Testimonial
"Elaine is absolutely the best, nicest, easiest to work with and the most fabulous statistician that I have worked with. I cannot say enough about her. I have been in academic medicine for 25 years now and founded a small biotech company. With Elaine's help on data, we were just purchased by Sanofi-Aventis, the 3rd largest pharma company! She helped our company so very much and no question was ever left unanswerable. You are making an excellent choice!"
- Resa Levetan, MD - Co-Founder, Cure DM
"Elaine is a wonderful statistics-oriented resource person who has both technical knowledge and business savvy. Having assisted my needs for a quality statistician, Elaine provided me with a well-planned and timely portfolio to aid in my research. She is very personable, and I highly recommend her impeccable data services."
Cirrelia Thaxton, Ph.D - Education
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