Plan, execute and interpret statistical analysis of clinical trials
This course in practical statistics for clinical trials covers protocol development and statistical analysis planning, statistical methods for testing for differences and estimating effect sizes, and the presentation and interpretation of results.
The primary focus of this course is to provide an understanding of the key statistical components required when conducting randomized clinical trials in accordance to the ICH E9 guideline, and for individuals to be able to demonstrate competencies in these components and apply them to clinical trials.
The overall aims of this module are to enable students:
To gain competence in execution and interpretation of core statistical techniques used by medical statisticians in randomized clinical trials, including:
- Understanding the key statistical components involved in the planning and conduct of clinical trials (i.e.):
- Awareness of different populations for analysis and understand which is appropriate to address specific research questions
- Awareness of different types of outcomes and be able to select the appropriate statistical technique for the type of outcome and study design
- Understanding and interpreting treatment effects, confidence intervals and P values
- Awareness of approaches to handling missing data and use of sensitivity analysis to test missing data assumptions
- Understanding how and when to conduct covariate adjustment and subgroup analysis
- Understanding how P values and confidence intervals are adjusted when multiplicity is present
- Understanding different types of trial designs and be able to choose the relevant design for a given question.
- Understanding issues to consider when designing a trial, including defining a primary outcome, carrying out sample size calculation, and analysing trial data.
- Demonstrating the ability to carry out sample size calculation for, at least, two arms parallel superiority trials
- Demonstrating the ability to prepare a statistical analysis plan
- Demonstrating the importance of interim analysis and stopping guidance for data monitoring committee.
- Understanding and applying statistical considerations when preparing a protocol or grant application.
This module assumes the students have at least some familiarity with the following:
- Distinction between continuous and categorical variables
- Interpretation of p values and statistical significance
- Interpretation of confidence intervals
- Concept of the Normal distribution
The last date for receipt of complete applications is 5pm Friday 12th April 2024. Regrettably, late applications cannot be accepted.