2 Hour Power Analysis for Sample Size Calculations:

Elaine Eisenbeisz
Instructor:
Elaine Eisenbeisz
Date:
16 Jul 2020
Time:
Thursday
12:00 PM EDT
Duration:
2 hr 0 Min
Webinar ID:
19507

Call to Action


Price Details
Live Version
$179.00   Single Participant
$369.00   Group Participant
Recorded Version
$229.00   Single Participant
$399.00   Group Participant
Value Packs
$429.00   Single Live + Recorded
$599.00  Group Live + Recorded

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.

 

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:

  • 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
Speaker Profile

Elaine Eisenbeisz is a private practice consultant based in Southern California. She has over 20 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.

Elaine’s love of numbers began in elementary school where she placed in regional and statewide mathematics competitions. She attended University of California, Riverside, as a National Science Foundation Scholar, where she earned a B.S. in Statistics with a minor in Quantitative Management, Accounting. Elaine completed her graduate certification in Applied Statistics with Texas A & M University. Gig ‘em Aggies! Currently, she is finishing her graduate work in Applied Statistics at Rochester Institute of Technology.

Elaine is a member of The American Statistical Association as well as many other professional organizations. She is also a member of the Mensa High IQ Society. Elaine is also a member in good standing with the Better Business Bureau.

Current areas of interest include Bayesian inference, simulation and bootstrapping techniques, and predictive modeling.

When she isn’t crunching numbers you can find Elaine digging in her garden, playing her violin, cooking, or playing board games with friends.

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