Clinical Trial Data Analysis
Course Index
32 Lessons · 3 Levels
End-to-end clinical trial data workflows in R & Python — CDISC SDTM/ADaM, survival analysis, MMRM, Bayesian adaptive designs, and TLF generation. Covers FDA/EMA/PMDA submissions, CDSCO India, real-world evidence & 4 production clinical builds.
32Lessons
3Levels
4Projects
FreeAccess
Level IFoundations, CDISC Standards & Study DesignLessons 1–10
LESSON 01
Clinical Trial Analysis Overview
LESSON 02
Clinical Trial Design & Phases
LESSON 03
CDISC SDTM: Data Tabulation Model
LESSON 04
CDISC ADaM: Analysis Data Model
LESSON 05
Python & R for Clinical Data
LESSON 06
EDC Systems & Data Collection
LESSON 07
Statistical Analysis Plan (SAP)
LESSON 08
Sample Size & Power Calculation
LESSON 09
Randomization & Blinding Methods
LESSON 10
Missing Data & Imputation Methods
Level IIStatistical Methods & Clinical ProgrammingLessons 11–22
LESSON 11
Survival Analysis: Kaplan-Meier
LESSON 12
Cox Proportional Hazards Model
LESSON 13
ANCOVA & Mixed Effects (MMRM)
LESSON 14
Logistic Regression for Binary Ends
LESSON 15
Adaptive Trial Designs
LESSON 16
Bayesian Methods in Clinical Trials
LESSON 17
Safety & Adverse Event Analysis
LESSON 18
Subgroup & Responder Analysis
LESSON 19
Biomarker & Patient Stratification
LESSON 20
TLF: Tables, Listings & Figures
LESSON 21
Clinical Study Report Programming
LESSON 22
Real-World Evidence & RWD Analysis
Level IIIRegulatory Submissions, Advanced Methods & ProjectsLessons 23–32
LESSON 23
FDA Regulatory Submissions with R
LESSON 24
EMA & PMDA Submission Standards
LESSON 25
CDSCO & India Trial Regulations
LESSON 26
Propensity Score & Causal Inference
LESSON 27
Meta-Analysis & Systematic Review
LESSON 28
AI & ML in Clinical Trials
LESSON 29
Build a Survival Analysis Dashboard
LESSON 30
Build an SDTM-to-ADaM Pipeline
LESSON 31
Build a TLF Automation Tool
LESSON 32
Build an FDA Submission Package