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
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
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.
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.
she isn’t crunching numbers you can find Elaine digging in her garden,
playing her violin, cooking, or playing board games with friends.
Lecture 1 (45 Mins) - Why Statistics?
Lecture 2 (45 Mins) - The many ways of interpretation
- 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 3 (45 Mins) - Common Statistical Tests
- Confidence intervals
- effect sizes
- Clinical vs. meaningful significance
Lecture 4 (45 Mins) - Bayesian Logic
- Comparative tests
- Regression analysis
- Non-parametric techniques
Lecture 5 (45 Mins) - Interpreting Statistics - Team Exercise
- A different way of thinking
- Bayesian methods and statistical significance
- Bayesian applications to diagnostics testing
- Bayesian applications to genetics
Lecture 6 (45 Mins) - Study power and sample size
- 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 7 (45 Mins) - Developing a Statistical Analysis Plan
- Review of p-value, significance level, effect size
- Formulas, software, and other resources for computing a sample size
Lecture 8 (45 Mins) - Specialized topics/Closing Comments/Q&A
- 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
- Comparing Survival Curves
- Pharmocokinetics/Pharmacodynamics (PK/PD)
- Taking a holistic view to study design and interpretation
- Question and Answer session
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