Introduction

This course covers advanced statistics in clinical trials and consists of protocol development and statistical analysis, use of statistical methods for analysing differences and estimating the effect of sizes. The main focus of this course is to provide training on key statistical concepts required for conducting randomized clinical trials based on ICH E9 guidelines which will enable individuals acquire skills in these components and apply them to clinical trials

Course Outcome

After the course, participants should be able to:

• Describe key statistical components involved in clinical trials
• Describe the effects of confidence intervals and P values
• Describe how and when to conduct covariate adjustment and subgroup analysis
• Describe how P values and confidence intervals are adjusted in multiplicity
• Described different types of clinical trial design and able to choose relevant design based on a given question
• Describe issue to take into considerations when designing clinical trial, such as sample size calculation and analysing clinical trial data
• Describe how to carry out sample size calculations
• Describe how to select appropriate methods to enable you handle missing data and apply them in clinical trial datasets
• Describe how to apply statistical concept when preparing a protocol or grant application

Course Modules

• Statistical Methods
• Randomized Control Trials Methodologies
• Statistical Analysis Planning
• Protocol Development
• Data science
• Communicating statistics to non-statisticians
• Practical Statistical where participants will be asked to design projects to address series of research questions associated with health issues in human. You will choose an appropriate number of individuals from the dataset and analysis the data using standard statistical computer packages such as Epilinfo, SPSS, and R. The report should be of high standard.

Teaching: The course will be taught through series of online tutorials, online formative exercises, series of pod-casts and discussion forums. It is compulsory that student take part in 90% of online tutorials. Self-directed learning is an essential component of this training. Electronic learning resources will be made available in our VLE.

Learning breakdown: Our online courses combine several elements to create a balanced blend of learning. Learners will be able to learn at their own pace during the week by viewing content, engaged in discussions, and completing assignments. It is expected that on the average, 8 to 10 hours per week is required for a course.

Assessment: Assessment for this course is based on summative assessment which counts to the module mark. Each summative assessment for a module will be made of a 1000 word essays, scientific article of high standard, 15 minutes presentations, and 6000 worded final assignment (practical statistics).

Duration: 12 weeks

Commitment: 8-10 hours per week as follows:

Eligibility:

The course is designed for:

• Graduate or have successfully completed a professional course
• Individuals with professional work experience in health-related institute
• Show evidence of previous statistical knowledge