Biostatistics for the Non-Statistician Training Course

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.

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.

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?

This seminar 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.

Emphasis 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 necessary.

SEMINAR OBJECTIVESWHO SHOULD ATTEND

The goal of this seminar is to teach you enough statistics to:

1. Understand the statistical portions of most articles in medical journals.
2. Do simple calculations, especially ones that help in interpreting published literature.
3. Avoid being misled by foolish findings.
4. Knowledge of which test when, why, and how.
5. Perform simple analyses in statistical software.
6. Communicate statistical findings to others more clearly.

• Physicians
• Clinical Research Associates
• Clinical Project Managers/Leaders
• Sponsors
• Regulatory Professionals who use statistical concepts/terminology in reporting
• Everyone working in the medical or health sciences, pharmaceutical and or nutraceutical industries, clinical trials, clinical research, and clinical research organizations, physicians, medical students, graduate students in the biological sciences, researchers, and medical writers who need to interpret statistical reports.

AGENDA

Recording 1:

Session 1: 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


Session 2: The many ways of interpretation
• Confidence intervals
• p-values
• effect sizes
• Clinical vs. meaningful significance


Session 3: Common Statistical Tests
• Comparative tests
• Regression analysis
• Non-parametric techniques


Session 4: Bayesian Logic
• A different way of thinking
• Bayesian methods and statistical significance
• Bayesian applications to diagnostics testing
• Bayesian applications to genetics

Recording 2:

Session 1: Systematic Reviews and Meta-Analysis
• Why perform a systematic reviews and/or meta-analysis?
• A bit of history and reasoning for systematic reviews and/or meta analysis
• Terminology
• Steps in performing a Systematic Review
• Steps in performing a Meta-Analysis


Session 2: Study power and sample size
• Review of p-value, significance level, effect size
• Formulas, software, and other resources for computing a sample size


Session 3: 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.


Session 4: Specialized topics & Other Tests
• Survival Curves and Cox Regression
• Logistic Regression
• Taking a holistic view to study design and interpretation
• Non-Parametric tests
• Test for equivalency
• Test for non-inferiority
• Question and Answer session

Course Directors: ELAINE EISENBEISZ

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.

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 received her Master’s Certification in Applied Statistcs from Texas A&M, and is currently finishing her graduate studies at Rochester Institute of Technology. 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.