Postgraduate Module Descriptor
SSIM913: Longitudinal Data Analysis
This module descriptor refers to the 2022/3 academic year.
Whilst the module’s precise content and order of syllabus coverage may vary, it is envisaged that it will include the following topics:
- Introduction to longitudinal data analysis and its applications.
- Testing assumptions in panel data analysis.
- Dealing with attrition and missing data.
- Fixed and random-effects models.
- Event history (Survival) models: What they are and when to use them.
- Survivor and hazard functions
I. Kaplan-Meier estimators
II. Life tables
- Continuous time models
- Discrete time models
- Using time-varying predictors
- Complex models: repeated events and competing risks models.
- Testing for unobserved heterogeneity (frailty models).
Learning and Teaching
This table provides an overview of how your hours of study for this module are allocated:
|Scheduled Learning and Teaching Activities||Guided independent study||Placement / study abroad|
...and this table provides a more detailed breakdown of the hours allocated to various study activities:
|Category||Hours of study time||Description|
|Scheduled Learning and Teaching||22||11x 2 hours of lectures, seminars and practical labs - lectures cover the main concepts and data analysis skills of the course.|
|Guided Independent Study||38||Reading and preparing for seminars (around 4-6 hours per week);|
|Guided Independent Study||90||researching and writing assessments and assignments (researching, planning and writing the course work).|
This module has online resources available via ELE (the Exeter Learning Environment).
UK Data Services - https://www.ukdataservice.ac.uk
Generations and Gender Programme - http://www.ggp-i.org/
ELE – College to provide hyperlink to appropriate pages
Other Learning Resources
There are a range of data sets that will be used in the course:
GGP: Waves 1-2.