The use of statistics in clinical trials insures a valid and robust study which minimizes bias in assessing the efficacy of new drug treatments or medical devices.
Why Should You Attend:
Participants in this 6-hour virtual seminar will learn the fundamentals of statistical theory, and how statistical concepts are applied in analysis and reporting of clinical research findings.
The objective of the seminar is to provide information that can be used immediately by personnel involved in analysis of clinical trial data. 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.
This seminar also provides a thorough review of the basics for those who need a refresher on statistical theory and types of statistical analyses
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 software are now available to professionals. However, this software 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.
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. Therefore, a basic/fundamental to intermediate understanding of statistics is all that is needed to understand and apply the information presented in this seminar.
- 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
- Confidence intervals
- Effect sizes
- Clinical vs. meaningful significance
- Comparative tests: t-tests, Analysis of Variance (ANOVA)
- Linear Regression analysis
- Non-parametric techniques
- Comparing Survival Curves and Cox Regression
- Logistic Regression
Ms Elaine Eisenbeisz,
Owner & Principal ,
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 the 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 Statistics from Texas A&M, and is currently finishing her graduate studies at Rochester Institute of Technology.
Who Should Attend
- Physicians Clinical Investigators
- Clinical Research Statisticians
- Clinical Research Coordinators
- Clinical Research Nurse Coordinators
- Clinical Research Associates/Assistants
- Clinical Project Managers/Leaders
- Study Managers
- Regulatory Professionals who use statistical concepts/terminology in reporting
- Medical Writers and others who need to interpret statistical reports.