Statistical Methods for Longitudinal Data
IDEAR Early career training program
Statistical Methods for Longitudinal Data
University College London, United Kingdom, April 16-20 2018
The aim of the course is to provide an introduction to and hands on experience of the analysis of longitudinal studies using:
- Random effects models for continuous outcomes
- Growth curve models
- Random effects models for binary data
- Event history models
- Multiple imputation for longitudinal data
Learning objectives
By the end of the course students will be able to:
- Use methods to identify between and within individual variation in outcomes
- Use and interpret models for longitudinal outcomes
- Understand the implications of missing data
- Perform multiple imputation for longitudinal data
- Propose, evaluate and select models
- Interpret and communicate results
Pre-requisites are:
- Experience of STATA or similar package
- Experience of linear and logistic regression
- Experience of data analysis
- Some knowledge of multiple imputation is desirable
There will be five sessions, each consisting of a 90-minute lecture followed by a 90-minute computer practical session. There will also be seminars, networking time and social events. Attendance at all sessions is compulsory.
Schedule Statistical Methods for Longitudinal Data
| Morning | Afternoon | |
|---|---|---|
| Monday | Random effects models for continuous outcomes | |
| Tuesday | Growth curve models | Seminar: Introduction to missing data |
| Wednesday | Event history analysis | Seminar: To be confirmed |
| Thursday | Random effects models for binary outcomes | Seminar: To be confirmed |
| Friday | Multiple imputation in longitudinal studies |
