Biostatistics for the Non-Statistician Seminar

Global Compliance Seminars

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.

Course Description

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?

Why you should attend:

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.

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.

Who will benefit:

Physicians
Clinical Research Associates
Clinical Project Managers/Leaders
Sponsors
Regulatory Professionals who use statistical concepts/terminology in reporting
Medical Writers who need to interpret statistical reports

Agenda:

Day 1 Schedule

Lecture 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

Lecture 2:

The many ways of interpretation

Confidence intervals
p-values
effect sizes
Clinical vs. meaningful significance

Lecture 3:

Common Statistical Tests

Comparative tests
Regression analysis
Non-parametric techniques

Lecture 4:

Bayesian Logic

A different way of thinking
Bayesian methods and statistical significance
Bayesian applications to diagnostics testing
Bayesian applications to genetics

Day 2 Schedule

Lecture 1:

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 2:

Study power and sample size

Review of p-value, significance level, effect size
Formulas, software, and other resources for computing a sample size

Lecture 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.

Lecture 4:

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

Speaker;

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.

In addition to her technical expertise, Elaine possesses a talent for conveying statistical concepts and results in a way that people can intuitively understand.

More Seminar Information

Global Compliance Panel
Summary	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.
Delivery Method	Seminar
Who Should Attend	• Physicians • Clinical Research Associates • Clinical Project Managers/Leaders • Sponsors • Regulatory Professionals who use statistical concepts/terminology in reporting • Medical Writers who need to interpret statistical reports