Module Code | STP80110 |
Module Name | Advanced Linear Models 1 |
ECTS Weighting | 5 ECTS |
Semester taught | Semester 1 |
Module Coordinator/s | Prof. Simon Wilson |
Module Learning Outcomes
- Distinguish between various approaches to estimating linear regression and linear mixed models, and identify how estimation approaches can be determined by the underlying theory of the model;
- Identify hierarchical structures in datasets, formulate the appropriate statistical linear mixed model to analyse the data, implement using statistical software as appropriate and interpret fitted models;
- Develop and implement non-parametric modelling approaches using statistical software as appropriate.;
Module Content
This module will cover the theory of linear regression and linear mixed models and their estimation methods; modelling repeated measures over time; various random effects models, including single random effects, multiple random effects, and random coefficient models; and non-parametric modelling approaches, to include splines and bootstrapping. An emphasis will be placed on learning how to implement these techniques using R or other statistical software. Multiple choice quizzes will be used as study aids to help students evaluate their knowledge throughout the semester.
Teaching and learning Methods
Online module consisting of 4 weekly sessions. Live tutorial sessions each week. All learning takes place through Blackboard.
Assessment Details
Assessment Component | Brief Description | Learning Outcomes Addressed | % of total | Week set | Week Due |
Final Exam | Take home exam | All | 100% | NA | NA |
| | | | | |
Reassessment Details
Take home exam, 100%.
Contact Hours and Indicative Student Workload
Contact Hours (lectures, labs, tutorials, meetings, etc.) | 30 |
Independent study (outside scheduled contact hours), broken down by: | 50 |
Preparation for classes and review of material (including preparation for examination, if applicable | 20 |
completion of assessments (including examination, if applicable) | 25 |
Total Hours | 125 |
Recommended Reading List
Material will be provided when needed.
Module Pre-requisites
ST8003, STP80110
Module Co-requisites
N/A
Module Website
Blackboard