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This four-day Online course is designed to give participants a good understanding of a range of techniques for longitudinal data analysis. It will use a mixture of theoretical sessions and practical sessions (using Stata) to illustrate concepts. Examples will primarily be taken from health research, such as the English Longitudinal Study of Ageing (ELSA).
The course will cover:
• Random effects models for continuous outcome
• Growth curve models
• Random effects models for binary data
• Event history analysis
Course leaders
Pre-requisites
Participants should have a good understanding and experience of applying and interpreting multiple linear regression models and logistic regression models. Participants should have prior experience of using a statistical package to analyse data such as Stata to gain the most out of the course. Please note we do not provide the statistical software.
Objectives
To provide students with the skills needed to design longitudinal research and conduct appropriate analyses using longitudinal data including the use of random effects models for repeated measures data and event history analysis.
Learning outcomes
By the end of this course students will be able to:
- Use methods to identify between and within individual variation in outcomes
- Use and interpret models for longitudinal outcomes
- Use and interpret growth curve models
- Use and interpret models for event history data
- Propose, evaluate and select models
- Interpret and communicate results
Certification
You will receive a certificate of attendance if you attend both days of the course. Please note the course does not receive UCL credits.
Cost and concessions
The fees are:
- Full rate: £250
- Reduced rate for PhD students at UK higher education institutes: £150
Dates
The course will run online from 10th - 13th November 2020, with a live session from 1pm - 3pm (UK time) everyday.
Reserve a place on this course
Last Booking Date: 1st November 2020