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10 Modules / ~100 pages
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~25 Modules / ~400 pages

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


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