# Power Analysis for Sample Size Calculations

Instructor: Elaine Eisenbeisz
Product ID: 705873

• Duration: 120 Min
In this webinar attendees will learn the statistical power analysis and techniques for determining sample size (a priori techniques) calculation. Also attendees will get work examples in the free to use G*Power software. Some code and demonstrations will be provided for powering studies and performing power analysis simulations in R software.
##### RECORDED TRAINING
Last Recorded Date: Dec-2018

\$249.00
1 Person Unlimited viewing for 6 month Recorded Link and Ref. material will be available in My CO Section
(For multiple locations contact Customer Care)

\$349.00
(For multiple locations contact Customer Care)

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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.”

Areas Covered in the Webinar:

• 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

Who Will Benefit:

• Physicians
• Clinical Investigator
• Clinical Research Associates
• Regulatory Professionals who use statistical concepts/terminology in reporting
• Medical Writers who need to interpret statistical reports
• IRB review board members
• DSMB members
Instructor Profile:

Elaine Eisenbeisz
Owner, Omega Statistics

Elaine Eisenbeisz is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California.

Elaine earned her B.S. in Statistics at UC Riverside and received her Master’s Certification in Applied Statistics from Texas A&M.

Elaine is a member in good standing with the American Statistical Association and a member of the Mensa High IQ Society. Omega Statistics holds an A+ rating with the Better Business Bureau.

Elaine has designed the methodology and analyzes data for numerous studies in the clinical, biotech, and health care fields. Elaine has also works as a contract statistician with private researchers and biotech start-ups as well as with larger companies such as Allergan, Nutrisystem and Rio Tinto Minerals. Throughout her tenure as a private practice statistician, she has published work with researchers and colleagues in peer-reviewed journals.

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