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Unit of study_
CLTR5007: Statistical Principles and Clinical Trials
2024 unit information
Statistical principles and concepts required to design clinical trials and analyse trial results will be introduced, including the appraisal of the appropriateness of analyses appearing in previous trial reports. Concepts which will be developed include an introduction to hypothesis testing, confidence interval estimation and understanding of univariable and adjusted analyses. Students will undertake analyses of study data where outcomes are continuous, binary and time-to-event variables. Concepts and issues involved in performing landmark analyses and in identification of key prognostic variables and their interpretation in a clinical trials context will be introduced. The basis for and understanding of sample size calculations for clinical trials will be covered. Analyses will be performed using Excel and statistical software. SPSS software will be supported but students may use any package they are familiar with and have available. It is the student's responsibility to purchase the software. Details will be given at the beginning of the semester.
Unit details and rules
Managing faculty or University school:
Medicine and Health
| Study level | Postgraduate |
|---|---|
| Academic unit | NHMRC Clinical Trials Centre |
| Credit points | 6 |
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Prerequisites:
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CLTR5001 |
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Corequisites:
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None |
| Prohibitions:
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None |
| Assumed knowledge:
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None |
At the completion of this unit, you should be able to:
- LO1. Understand the statistical principles behind the analysis and interpretation of trial data, including confidence intervals, hypothesis testing and p-values and appropriate presentation and interpretation of results.
- LO2. Present and interpret summary data for continuous outcomes. Understand and test the assumptions required for analysis of continuous outcomes. Perform statistical comparisons of continuous outcomes between two groups. Perform and interpret adjusted analyses of continuous outcomes.
- LO3. Present and interpret summary data for binary outcomes. Perform statistical comparisons of binary outcomes between two groups. Perform and interpret adjusted analyses of binary outcomes. Be aware of suitable analyses of binary outcomes when data are sparse.
- LO4. Present and interpret summary data for time-to-event outcomes. Understand and test the assumptions required for analysis of time-to-event outcomes. Perform and interpret statistical comparisons of time-to-event outcomes between two groups. Perform and interpret adjusted analyses of time-to-event outcomes.
- LO5. Understand the connection between statistical hypothesis testing and significance level, power and sample size. Perform sample size calculations for comparing continuous, binary and time-to-event outcomes in two groups. Understand and adjust for the impact of non-adherence to treatment and loss to follow-up in sample size calculations.
- LO6. Critically appraise sample size calculations in a clinical trial protocol. Critically appraise and interpret statistical analyses of clinical trial data.
Unit availability
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The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
| Session | MoA ? | Location | Outline ? |
|---|---|---|---|
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Semester 2 2024
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Online | Camperdown/Darlington, Sydney |
Outline unavailable
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Modes of attendance (MoA)
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Important enrolment information
Departmental permission requirements
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