Further Topics in Statistical Modelling

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Recognise the basic statistical theory underpinning the models presented in the course.
• Use appropriate statistical tools for assessing goodness of fit and choosing among competing modelling techniques.
• Contrast statistical modelling techniques widely used for predictive purposes.
• Employ Multilevel (Mixed effects) and Marginal models for the analysis of hierarchical and longitudinal data.
• Interpret the results of statistical analyses in non-technical language.

• Main statistical models for Hierarchical/Longitudinal data
• Multilevel models: Random intercepts and Random slopes, use of contextual variables
• Multilevel and Marginal models for Longitudinal data
• Multilevel models for a binary response
• The predictive approach. Cross-validation and the Bootstrap
• Additional modelling techniques. E.g., non-parametric regression, penalised regression, GAMs, CART

Teaching will be delivered by a mixture of synchronous and asynchronous online methods, which may include lectures, quizzes, discussion boards, workshop activities, exercises, and videos. A range of resources will also be provided for further self-directed study. Face-to-face teaching opportunities will be explored depending on circumstances and feasbility.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.