Advanced Biostatistics for HDS
Module Aims: This required module for the HDS specialisation aims to provide students with a knowledge of more advanced statistical methods and further experience of analysing data using statistical software.
Module Learning Outcomes:
By the end of the module, students should be able to:
- Assess the fit of simple models and choose between alternative models
- Identify instances of overfitting, choose and apply appropriate methods for dealing with this problem, and discuss the results obtained
- Identify when methods for clustered data are appropriate, choose and fit appropriate models, and interpret the results
- Identify when problems of multiple testing arise, choose and apply suitable solutions
- Discuss problems caused by missing values, discuss the choice of methods for analysing incomplete data sets, apply these methods and interpret the results
- Choose and apply suitable methods for dimension reduction and clustering, and discuss the results obtained
- Choose and apply suitable multi-state models, and interpret the results.
Pre-requisites: Statistics for HDS.
Teaching Strategy: Lectures, computer practicals. Some preliminary reading may be required.
Assessment: Take-home exercise at the end of the module involving analysis of dataset(s) using R. Students will have 1 week to complete the exercise.
Module Length: 4 days