Statistical Analysis Issues That All Clinicians Must Know

Bracy Analytics extensive experience in the Clinical Trials arena has positioned us uniquely to provide training for Clinicians specifically geared to understanding and dealing with Statistical Analysis Issues. This course is appropriate for Clinicians of all experience levels.

Course Description

This course is appropriate for anyone who is involved in designing, planning, participating or conducting a clinical trial. The course addresses the many statistical issues and concerns that arise during the planning, implementing and conclusion of a clinical trial. Presented in a concise and understandable way for non-statisticians, clinicians will realize the importance and significance of the incorporation of many disciplines in clinical research. Understanding these issues allows a Clinician to accomplish our collective goal in medical research: To improve the lives and health of our citizens.

Course Content

1. Study Design
1. The need for a Control Group
2. Blinding (Single and Double)
3. Randomization
1. What is it?
2. Different Methods/Tools for randomizing subjects
4. Designing a clinical trial around a study question/hypothesis
1. Determining duration of study in order to produce measurable effect on the primary effects
2. Statistical problems and issues posed by multiple analysis (endpoints) in a trial.
5. What is a Statistical Analysis Plan (SAP)?
1. When should it be written.
2. What is in a SAP.
6. Power and Sample Size
1. What is Power
2. Determining a sample size
3. How are these concepts related
2. Statistical Monitoring of a clinical trial
1. The need for Safety Monitoring Boards (DSMBs) or Data Monitoring Committees (DMCs)
1. History
2. Purpose
2. Monitoring Procedures
1. O'Brian & Fleming
2. Lan-DeMets Monitoring Boundaries
3. Conditional Power (Halperin)
4. Bayesian Methods
5. Path Analysis
6. Group Sequential Analysis
7. Others
3. Common Statistical Methods and Concepts
1. T-Test (one-sample and two-sample)
2. Z-Test (Normal Distribution)
3. ANOVA and Analysis of Covariance concepts
4. Parametric vs. Non-Parametric Statistics
5. Significance Level
6. Means and Variance
7. Determining Statistical Distributions
8. Different Software Packages