Advanced Biostatistics for Medical Research: Statistical Analysis in Clinical Trials
( 26 Modules )
Module #1 Introduction to Clinical Trials Overview of clinical trials, types of trials, and phases of drug development
Module #2 Design of Clinical Trials Parallel group designs, crossover designs, and factorial designs
Module #3 Sample Size Calculation Methods for calculating sample size, including power analysis and precision-based methods
Module #4 Hypothesis Testing Introduction to hypothesis testing, types of errors, and p-values
Module #5 Confounding and Effect Modification Understanding confounding variables and effect modification in clinical trials
Module #6 Correlation and Regression Analysis Simple and multiple linear regression, correlation coefficients, and model assumptions
Module #7 Survival Analysis Introduction to survival analysis, Kaplan-Meier estimates, and Cox proportional hazards model
Module #8 Longitudinal Data Analysis Introduction to longitudinal data, linear mixed effects models, and generalized estimating equations
Module #9 Missing Data in Clinical Trials Types of missing data, methods for handling missing data, and multiple imputation
Module #10 Intention-to-Treat Principle Understanding the intention-to-treat principle and its application in clinical trials
Module #11 Interim Analysis and Stopping Rules Introduction to interim analysis, group sequential designs, and stopping rules
Module #12 Multiplicity Adjustment Methods for adjusting for multiple testing, including Bonferroni and Holm-Bonferroni methods
Module #13 Subgroup Analysis Challenges and limitations of subgroup analysis, and methods for subgroup identification
Module #14 Non-Inferiority and Equivalence Trials Design and analysis of non-inferiority and equivalence trials
Module #15 Biomarker Analysis Introduction to biomarker analysis, predictive modeling, and personalized medicine
Module #16 Adaptive Design Introduction to adaptive design, adaptive randomization, and biomarker-adaptive designs
Module #17 Real-World Evidence Introduction to real-world evidence, observational studies, and pragmatic trials
Module #18 Data Visualization in Clinical Trials Best practices for data visualization in clinical trials, including graphics and tables
Module #19 Regulatory Considerations Regulatory guidelines for clinical trials, including FDA and EMA guidelines
Module #20 Ethical Considerations Ethical principles for clinical trials, including informed consent and confidentiality
Module #21 Case Studies in Clinical Trials Real-world examples of clinical trials, including successes and challenges
Module #22 Statistical Software for Clinical Trials Introduction to software packages commonly used in clinical trials, including R and SAS
Module #23 Collaboration and Communication Effective collaboration and communication strategies for biostatisticians and clinicians
Module #24 Future Directions in Clinical Trials Emerging trends and innovations in clinical trials, including artificial intelligence and machine learning
Module #25 Practice Exercises and Projects Hands-on practice exercises and projects to apply advanced biostatistical concepts to real-world data
Module #26 Course Wrap-Up & Conclusion Planning next steps in Advanced Biostatistics for Medical Research: Statistical Analysis in Clinical Trials career
