Introduction to Multilevel Modelling Using MLwiN, R, or Stata

Please note this event is not run by the SWDTP. Please direct enquiries to Lucy Haslam at the University of Bristol Centre for Multilevel Modelling: lucy.haslam@bristol.ac.uk

Please note the closing date for applications is 23rd November 2025

Professor George Leckie and Professor William Browne

This three-day course provides an introduction to multilevel modelling and includes software practicals in your choice of software: MLwiN, R, or Stata. We focus on multilevel modelling for continuous and binary responses (dependent or outcome variables) when the data are clustered (nested or hierarchical). These models can be viewed as an extension of conventional linear and logistic regression models to account for and learn from the clustering in the data. Such models are appropriate when, for example, analysing exam scores of students nested within schools, or health outcomes of patients nested within hospitals. Special interest lies in disentangling social processes operating at different levels of analysis by decomposing the within- from the between-cluster effects of covariates (explanatory or predictor variables). Longitudinal data are also clustered, with repeated measurements on individuals or multiple panel waves per survey respondent. Throughout the course we emphasize how to interpret multilevel models and the types of research question they can be used to explore.

“The course was really excellent – clearly structured and in a logical order. Speakers were fantastic.”

“The course was excellent – far exceeded expectations. The course has given me the confidence to use MLM, something I very much lacked before. I feel I understand the theory behind MLM, why each stage is so important, and the various interpretations. Without this course I would be lost. I cannot thank you all enough.”

“This was a beautifully constructed course. It was clear throughout that careful thought had been given to providing a balance between lecture content, time for questions and discussion, and practical sessions. Both George and Bill delivered fantastic lectures – explanations were clear and thorough (including critiques of each approach) and content built up in complexity over time with plenty of worked examples of different kinds. The course was superb – can’t rate it highly enough.”

“I thought it was a really good double act between George and Bill – they are both hugely knowledgeable so having one person focused on the slides and the other manning the chat was a good approach as it meant the teaching didn’t get derailed by people’s questions.”

“Both George and Bill have excellent presentation styles. I really liked that they ‘riffed’ off of each other with gentle humour.”

The course will consist of a 2:1 mix of lectures and hands-on practical sessions applying the taught methods to real datasets. The instructors alternate the lecturing. The lectures are software independent. Each lecture is immediately followed by a software practical giving participants the chance to replicate the presented analyses and to consolidate their knowledge. The practicals are offered in participants’ choice of MLwiN, R, or Stata and are self-directed: participants complete the practicals at their own pace. At the end of each practical session the instructors demo the different software. In both the lectures and practicals, participants have opportunities to interact with the instructors.

The course will be delivered online via the freely accessible Zoom platform. The lectures will be delivered live. Participants can ask questions via Zoom’s text-based chat facility and these will be monitored and answered by the instructor not presenting or relayed to the instructor presenting to answer live.

Participants are encouraged to join the lectures live, but recordings of the lectures will be made available shortly afterwards for twelve weeks following the course if participants are unable to attend at the scheduled time. After twelve weeks, video access will end and will not be extended.

During the practicals, participants can also speak with the instructors. Participants can use these opportunities to ask specific questions about the course material or about multilevel modelling related to their own research. Each software package will be demonstrated in a different breakout room.

Participants will be emailed in advance with comprehensive PDF copies of the lecture slides together with point-and-click instructions and datasets for MLwiN, and annotated syntax files and datasets for R and Stata. During the practicals, participants are encouraged to view the lecture slides on a second screen (or tablet etc.), else print copies out to have in front of them. Those choosing to use MLwiN may also want to view the point-and-click instructions on a second screen, else print them out.

For those choosing to use MLwiN, we will provide instructions as to how to download and install the free teaching version of this software. For those wishing to use R or Stata we assume you are already users of these software so have them installed.

We assume no prior knowledge of multilevel modelling. However, participants should be familiar with estimating and interpreting linear regression models, including the writing and interpretation of model equations, hypothesis testing and model selection, and the use and interpretation of dummy variables and interaction terms.

We will email in advance a pre-recorded lecture, to be completed at the participant’s leisure, which provides a review of linear regression accompanied with software instructions and datasets to replicate the analyses in MLwiN, R, and Stata.

For those choosing to use MLwiN, we assume no prior knowledge of using this software and so we provide step-by-step instructions to allow you to replicate all presented analyses in MLwiN. For those choosing R or Stata, we assume you are already users of these software and so know the basics.

The course starts and ends each day at 09:15 and 16:00 with a 30-minute morning break and a one-hour break for lunch from 13:00 to 14:00.

Please note, in order to be eligible for the reduced pricing brackets please submit your application using your UK academic/organisational email address.

A full refund will be given if cancellation occurs two weeks prior to the event. No refund is given after this date. By completing the application form, you are accepting these cancellation terms.

If you would like to attend the workshop, please complete and submit the online booking form (see below). Please note the closing date for applications is 23rd November 2025.

Applications will be processed on a rolling basis, once a week, until the application deadline. A link to the University of Bristol’s online shop will be provided and your place on the course will be confirmed upon successful payment.

If you have any queries, please email info-cmm@bristol.ac.uk.

Please click here to read the booking terms and conditions before completing the booking form. Note that it is the participant’s responsibility to ensure that Zoom and their choice of MLwiN, R, or Stata software is up-to-date and works on their computer in advance of the course, as the Centre for Multilevel Modelling is unable to provide technical support.

MLwiN is dedicated multilevel modelling software developed by our research team for more than 30 years. On this course we will be using the free teaching version of MLwiN. This version works with all the datasets used on the course and a wide range of other teaching datasets which come with the software. We will email you the teaching version prior to the start of the course.

Should you wish to use MLwiN after the course with your own data, you will need to use the regular version of MLwiN. This is free to UK academics (but without user support) reflecting long periods of funding from the UK’s Economic and Social science Research Council (ESRC). For all other users, there is a 30-day trial version, but after that you will have to purchase MLwiN if you wish to continue using it to analyse your own data. There are various price options available. http://www.bristol.ac.uk/cmm/software/mlwin/

MLwiN is Windows software, but can be run on Mac via the Wine software or through a virtual machine such as Parallels, depending on the Mac model and version of MacOS on your machine.