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:

1. Assess the fit of simple models and choose between alternative models
2. Identify instances of overfitting, choose and apply appropriate methods for dealing with this problem, and discuss the results obtained
3. Identify when methods for clustered data are appropriate, choose and fit appropriate models, and interpret the results
4. Identify when problems of multiple testing arise, choose and apply suitable solutions
5. Discuss problems caused by missing values, discuss the choice of methods for analysing incomplete data sets, apply these methods and interpret the results
6. Choose and apply suitable methods for dimension reduction and clustering, and discuss the results obtained
7. 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