Research Methods for Multilevel data online course
Date:
19/03/2025 - 21/03/2025
Organised by:
UCL
Presenter:
Dr Giorgio Di Gessa
Level:
Intermediate (some prior knowledge)
Contact:
Venue: Online
Description:
This course is for anyone needing to analyse multilevel data. When your data are structured in nested groups (like students within classrooms, patients within hospitals, or individuals within regions), and you want to understand how factors at both levels influence the outcome variable, appropriate statistical techniques that account for this hierarchical structure should be used. The aim of the course is to provide an introduction to the analysis of multilevel data and to the selection of appropriate multilevel models based on your research questions, including whether to allow intercepts or slopes to vary across groups (random effects vs. fixed effects). Practical examples of how to successfully fit multilevel models and interpret results will be presented, using the statistical package Stata.
There will be 6 sessions taught via Zoom. Every day, a theoretical lecture will be followed by a computer practical session (Stata) for attendees to see how to perform statistical analyses and interpret and evaluate the results. All material (including slides, datasets, .do files, and solutions) will be available to attendees prior to the start of the course.
The course would be suitable for full-time and part-time students in any year of study and members of staff. It is aimed at those using quantitative data in any scientific or educational research area. Attendees must have a basic knowledge of regression modelling techniques.
Content
Introduction to clustered data;
The distinction between levels and variables;
The distinction between fixed and random classifications;
Random Intercept Models;
Random Slope Models;
Level 1 and 2 explanatory variables;
Cross-level interactions.
Cost:
£200 full price
£100 students
Website and registration:
Region:
Greater London
Keywords:
Quantitative Data Handling and Data Analysis, Multilevel Modelling , Hierarchical models, Mixed models, Random effects
Related publications and presentations from our eprints archive:
Quantitative Data Handling and Data Analysis
Multilevel Modelling
Hierarchical models
Mixed models
Random effects