Statistics is a useful decision making tool in the clinical research arena. When working in a field where a p-value can determine the next steps on development of a drug or procedure, it is imperative that decision makers understand the theory and application of statistics.
Why you should attend
Many statistical softwares are now available to professionals. However,
these softwares were developed for statisticians and can often be
daunting to non-statisticians. How do you know if you are pressing the
right key, let alone performing the best test?
provides a non-mathematical introduction to biostatistics and is
designed for non-statisticians. And it will benefit professionals who
must understand and work with study design and interpretation of
findings in a clinical or biotechnology setting.
The focus of the
seminar is to give you the information and skills necessary to
understand statistical concepts and findings as applies to clinical
research, and to confidently convey the information to others.
will be placed on the actual statistical (a) concepts, (b) application,
and (c) interpretation, and not on mathematical formulas or actual data
analysis. A basic understanding of statistics is desired, but not
Who Will Benefit
- Clinical Research Associates
- Clinical Project Managers/Leaders
- Regulatory Professionals who use statistical concepts/terminology in reporting
- Medical Writers who need to interpret statistical reports
Lecture 1 (45 Mins) - Why Statistics?
- Do we really need statistical tests?
- Sample vs. Population
- I'm a statistician not a magician! What statistics can and can't do
- Descriptive statistics and measures of variability
Lecture 2 (45 Mins) - The many ways of interpretation
- Confidence intervals
- effect sizes
- Clinical vs. meaningful significance
Lecture 3 (45 Mins) - Common Statistical Tests
- Comparative tests
- Regression analysis
- Non-parametric techniques
Lecture 4 (45 Mins) - Bayesian Logic
- A different way of thinking
- Bayesian methods and statistical significance
- Bayesian applications to diagnostics testing
- Bayesian applications to genetics
Lecture 5 (45 Mins) - Interpreting Statistics - Team Exercise
- Team Exercise: Review a scientific paper and learn how to
- Interpret statistical jargon
- Look for reproducibility, transparency, bias, and limitations
- Convey information coherently to non-statisticians
Lecture 6 (45 Mins) - Study power and sample size
- Review of p-value, significance level, effect size
- Formulas, software, and other resources for computing a sample size
Lecture 7 (45 Mins) - Developing a Statistical Analysis Plan
- Using FDA guidance as a foundation, learn the steps and criteria needed to develop a statistical analysis plan (SAP)
- An SAP template will be given to all attendees
Lecture 8 (45 Mins) - Specialized topics/Closing Comments/Q&A
- Comparing Survival Curves
- Pharmocokinetics/Pharmacodynamics (PK/PD)
- Taking a holistic view to study design and interpretation
- Question and Answer session
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.
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. Elaine received her Master’s Certification in Applied Statistics from Texas A&M and continues to learn from her practice. Elaine is a member in good standing with the American Statistical Association as well as many other professional organizations. She is also a member of the Mensa High IQ Society. Omega Statistics holds an A+ rating with the Better Business Bureau.
Elaine has designed the methodology for numerous studies in the clinical, biotech, and health care fields. She designs and analyzes studies as a contract statistician for pharmaceutical and proton therapy research. She also works on nutriceutical and fitness studies. Elaine works as a contract statistician with numerous private researchers, CRO’s and biotech start-ups as well as with larger companies such as Allergan, Nutri-System, and Rio Tinto Minerals.
Not only is Elaine well versed in statistical methodology and analysis, she works well with project teams. Throughout her tenure as a private practice statistician, she has published work with researchers and colleagues in peer-reviewed journals. Please visit the Omega Statistics website at www.OmegaStatistics.com to learn more about Elaine and Omega Statistics.