POPH90014 Chap.7 Randomised Controlled Trials
Randomised Controlled Trials
Define random allocation
The course material gives this chapter a concrete anchor: Week 7 evaluates trials through design, ethics, ITT and risk-of-bias domains.
That random allocation anchor controls how intention-to-treat analysis is explained and how risk of bias is tested in changed practice.
Randomised Controlled Trials is a quantitative decision problem built from random allocation, intention-to-treat analysis and risk of bias.
The aim is to critique allocation, adherence, outcome assessment and reporting in an RCT; a numerical result earns meaning only when the variables, units, assumptions and comparison are all explicit.
Begin with random allocation: state what quantity it represents, the scale on which it is measured and the condition under which it changes.
Then map every symbol in the Randomised Controlled Trials formula checkpoint to random allocation before calculation begins.
Formula checkpoint: random allocation
Outcomes and denominators follow original random assignment for an ITT risk ratio.
Trace intention-to-treat analysis
Next connect intention-to-treat analysis to the calculation.
Show the intention-to-treat analysis transformation line by line, preserve units and signs, and make any denominator or baseline visible. A intention-to-treat analysis calculator output is not a method; the reader must be able to reconstruct why that operation answers the question.
Use risk of bias to interpret or stress-test the result.
Ask whether the risk of bias magnitude is plausible, whether a boundary case behaves as expected and which conclusion would reverse if an assumption changed. This is where computation becomes analysis rather than arithmetic.
When the task is to critique allocation, adherence, outcome assessment and reporting in an RCT, separate inputs supplied by the problem from quantities you derive.
Then report the risk of bias result in the language of the course and attach the relevant uncertainty, limitation or decision consequence.
Test with risk of bias
Build a representation check before solving.
Put random allocation, intention-to-treat analysis and risk of bias into a small symbol-and-units table, mark which values are observed and which are calculated, and predict the direction of the result before doing arithmetic. A sign, scale or unit mismatch in random allocation then becomes visible at setup instead of being hidden inside a polished final number.
Run one sensitivity test after the baseline answer.
Change the input most closely connected to intention-to-treat analysis, hold the remaining assumptions fixed and recompute only the affected steps. Explain whether the movement in risk of bias matches the mechanism.
This intention-to-treat analysis sensitivity shows which assumption controls the conclusion and prevents a single scenario from being presented as universal.
Use a three-column random allocation error log for POPH90014: translation error, calculation error and interpretation error.
Record the exact line where the intention-to-treat analysis solution first diverged, rewrite that line, and check it with a limiting case or an independent calculation.
Correcting the first failed intention-to-treat analysis move is more useful than copying the complete solution again.
Transfer to Randomised Controlled Trials
A complete response should make the task visible before the detail: identify what must be decided, define the relevant terms, connect the evidence to intention-to-treat analysis, and use risk of bias to test the result.
The final sentence about risk of bias should answer the question actually asked rather than merely repeat the topic.
The controlling limit is specific: randomisation does not repair attrition, measurement or selective-reporting bias.
Keep that risk of bias limit beside the worked example, because it separates a careful POPH90014 answer from one that sounds confident but claims more than the task or evidence supports.
For revision, retrieve random allocation, intention-to-treat analysis and risk of bias without notes, explain their relationship aloud, then complete a changed version of the application: critique allocation, adherence, outcome assessment and reporting in an RCT.
Record the first failed intention-to-treat analysis reasoning move and repair it before attempting another case.
What this chapter covers
- 01
Random allocation
- 02
Intention-to-treat analysis
- 03
Risk of bias
- 04
Applying random allocation
- 05
Limits of intention-to-treat analysis and risk of bias
Analyse by assigned group
- 1Retain all observed participants by original assignment.
- 1Compute risks by assigned arm.
- 1Contrast with per-protocol selection.
- 1Explain the estimand.
Key terms
- Random allocation
- Chance mechanism assigning eligible participants to intervention groups. This chapter uses the concept when students critique allocation, adherence, outcome assessment and reporting in an RCT. Use this definition when the task is to critique allocation, adherence, outcome assessment and reporting in an RCT.
- Intention-to-treat analysis
- Analysis retaining participants in their assigned groups regardless of adherence. It helps explain the reasoning required to critique allocation, adherence, outcome assessment and reporting in an RCT. Use this definition when the task is to critique allocation, adherence, outcome assessment and reporting in an RCT.
- Risk of bias
- Systematic process capable of shifting an estimated intervention effect. Its limit matters because randomisation does not repair attrition, measurement or selective-reporting bias. Use this definition when the task is to critique allocation, adherence, outcome assessment and reporting in an RCT.
Randomised Controlled Trials FAQ
How does random allocation help a student critique allocation, adherence, outcome assessment and reporting in an RCT?
Critique allocation, adherence, outcome assessment and reporting in an RCT. Week 7 evaluates trials through design, ethics, ITT and risk-of-bias domains. Chance mechanism assigning eligible participants to intervention groups. This chapter uses the concept when students critique allocation, adherence, outcome assessment and reporting in an RCT.
Does randomisation repair attrition, measurement or selective-reporting bias?
Randomisation does not repair attrition, measurement or selective-reporting bias. Analysis retaining participants in their assigned groups regardless of adherence. It helps explain the reasoning required to critique allocation, adherence, outcome assessment and reporting in an RCT.
Once differential loss to follow-up is introduced, how should a student reassess exchangeability?
An ITT analysis keeps the 15 non-adherent participants in the intervention arm, preserving the allocation-based comparison for the treatment-policy effect. Randomisation does not repair attrition, measurement or selective-reporting bias.
Exam move
Reconstruct the relationship among random allocation, intention-to-treat analysis and risk of bias; complete the chapter application without notes; then test the result against this limit: randomisation does not repair attrition, measurement or selective-reporting bias.
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