Free 16-Lesson Course
Design of Clinical StudiesFrom the first question to the final report
Design of Clinical Studies is a sixteen-lecture course on how clinical trials are designed, sized, run, monitored, analyzed and reported. Every lesson follows one fictional trial, the Oakhaven Adherence Trial, from its first question to its final report, using invented numbers chosen so every calculation can be redone by hand. It is built for MPH and MS students, clinical research coordinators, investigators starting their first trial and epidemiology staff. By the end, a learner can write the design section of a protocol, from the question and estimand through allocation, sample size, monitoring and analysis, and can read a trial report critically. The course is education only; it uses no real data and cites no real studies.
Free Course
Design of
Clinical Studies
Produced by Subthesis
Course at a glance
16
Video lessons
Publishing daily from November 17, 2026
1
Fictional trial
Every calculation can be redone by hand
160
Quiz questions
Ten per lesson, every answer explained
Course outline
16 lessons following one fictional trial from question to report · click any lesson to start
- Lesson 0
What a Clinical Trial Is, and Why We Randomize Participants
- Distinguish experimental from observational studies by who assigns the intervention
- Explain confounding by indication with a simple arrow diagram
- Describe what adjustment can and cannot fix in an observational comparison
- Lesson 1
Research Question to Protocol: Objectives, Estimands, and SAP
- Write a trial question with population, intervention, comparison, endpoint and time
- Turn a question into one primary objective and ranked secondaries
- Write an estimand with a strategy for each intercurrent event
- Lesson 2
Clinical Trial Phases Explained: First-in-Human to Phase IV
- State the question, typical size and duration of each phase
- Walk a dose-finding cohort through the three-plus-three rule to the maximum tolerated dose
- Explain why a promising phase two result is not evidence of benefit
- Lesson 3
Who Gets Into a Trial: Eligibility, Run-In, Regression to Mean
- Write inclusion and exclusion criteria with a reason for every line
- Weigh homogeneity against generalizability
- Build a recruitment plan from a screening funnel and a monthly target
- Lesson 4
Choosing the Control Group: Placebo, Usual Care, and Equipoise
- Specify an intervention by content, dose, delivery, duration and adherence rule
- Match each of six control options to the question it answers
- Separate expectation and attention from natural course, regression and measurement in a control arm
- Lesson 5
Trial Endpoints: Primary, Composite, Surrogate, and Safety
- Turn an outcome into an endpoint measured in everyone at a fixed time by a fixed rule
- Classify endpoints and state the risk ratio, mean difference or hazard ratio for each
- Explain censoring in a time-to-event endpoint
- Lesson 6
Randomization Methods: Simple, Blocked, Stratified, Concealed
- State the three things randomization buys and the one it does not guarantee
- Show how simple randomization can drift out of balance
- List the six sequences of a block of four and explain block predictability
- Lesson 7
Blinding in Clinical Trials: Who Is Masked, and Why It Matters
- Name the bias introduced when participants, clinicians, assessors, analysts or the committee know the arm
- Describe how a matching placebo and a sham procedure are built
- Plan an open-label blinded-endpoint design when the intervention cannot be hidden
- Lesson 8
Parallel, Factorial, and Cluster Randomized Trials Explained
- Explain why the parallel-group design is the default
- Read the two main effects of a factorial and check the no-interaction assumption
- Describe what a large simple trial keeps and gives up
- Lesson 9
Crossover, Non-Inferiority, and Adaptive Designs Explained
- Explain why a crossover needs fewer participants and when carryover rules it out
- State what an n-of-1 trial can and cannot conclude
- Read non-inferior, inconclusive and inferior verdicts from an interval and a margin
- Lesson 10
Sample Size and Power I: The Ingredients and the Two Formulas
- Name the four ingredients and identify the one that is a clinical judgment
- Define type one and type two errors and power
- Derive the 16 and 21 multipliers from the z values
- Lesson 11
Sample Size II: Time-to-Event, Non-Inferiority, Cluster, Loss
- Compute the events needed for a hazard ratio and convert events to participants
- Compute a non-inferiority sample size from the margin
- Turn a per-arm size into a number of clinics with the design effect
- Lesson 12
Running the Trial: Data Collection, Quality, Safety Reporting
- Lay out the conduct timeline from set-up to report
- Design a case report form field with its six parts
- Place range checks, logic checks, queries and source verification along the data flow
- Lesson 13
Interim Analysis and Stopping Rules: The Monitoring Committee
- Give the three valid reasons to look at accumulating data
- Explain how repeated looks inflate the type one error and how alpha is spent
- Apply a conservative early boundary to an interim result
- Lesson 14
Intention to Treat, Subgroups, Missing Data, and Estimands
- Compute a risk ratio, risk difference and number needed to treat by intention to treat
- Explain why a per-protocol contrast exaggerates the effect
- Choose pre-specified baseline covariates and avoid post-randomization ones
- Lesson 15
Reading and Reporting a Trial: Flow, Registration, Integrity
- Interpret an estimate and interval for importance, not just significance
- Draw a participant flow diagram that adds up from assessed to analyzed
- Build a results table that names the analysis population in every row
Questions, corrections, or a topic the course should cover?
Who it is for: MPH and MS students, clinical research coordinators, new trial investigators and epidemiology staff with a basic grounding in epidemiology and algebra.
Design of Clinical Studies is education only. Every lesson follows the fictional Oakhaven Adherence Trial with invented numbers; the course uses no real data and cites no real studies.