Upcoming workshops
Introduction to Multilevel Modelling Using MLwiN, R, or Stata, 9 - 11 July 2025, Online via Zoom
Run in partnership with NCRM
Instructors
Professor George Leckie and Professor William Browne
Summary
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.
Testimonials
“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.”
Topics
- Overview of multilevel modelling
- Variance-components models
- Random-intercept models with covariates
- Between- and within-effects of level-1 covariates
- Random-coefficient models
- Growth-curve models
- Three-level models
- Review of single-level logistic regression
- Two-level logistic regression
Format
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.
Zoom
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.
Materials
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.
Software
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.
Pre-requisites
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.
Timings
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.
Fees
- For UK-registered MSc and PhD students - £180
- For UK university academics, UK public sector staff, and staff at UK registered charity organisations - £360
- For all other participants - £660
Please note, in order to be eligible for the reduced pricing brackets please submit your application using your UK academic/organisational email address.
Cancellation/refunds
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.
Applications
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 25th May 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.
Terms and conditions
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
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. http://www.bristol.ac.uk/cmm/software/mlwin/features/sysreq.html#unix .
An Introduction to Multilevel Modelling for Intersectionality Research: The MAIHDA Approach, Thursday 19th June 2025, In-Person at the School of Education, University of Bristol
Run in partnership with the University of Sheffield, NCRM, and the ESRC.
Instructors
Professor George Leckie (University of Bristol) and Dr Andrew Bell (University of Sheffield)
Summary
Multilevel models allow researchers to analyse data with a clustered structure—for example, pupils nested within schools or individuals within neighbourhoods. Recently, a variation of multilevel modelling has been developed to study intersectional inequalities in individual outcomes. The Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) approach nests individuals within their intersectional strata—that is, their unique combination of sociodemographic identity categories, such as gender, age, ethnicity, and social class. This method holds great potential for uncovering and understanding intersectional inequalities, where multiple social identities interact in complex ways to shape societal (dis)advantages.
This free, one-day training course will provide a brief introduction to multilevel modelling, followed by an overview of the intersectional MAIHDA approach. The course will cover the basics of two-level random-intercept multilevel models, how to apply this model within the MAIHDA framework, key statistics generated by the approach, examples from the literature, and guidance on visualizing the results.
Topics
- Overview of multilevel modelling
- The two-level random-intercept model
- Intersectionality: theory and practice
- Ways of statistically identifying intersectional inequalities: dummy variables and interactions
- The MAIHDA approach
- Visualising results from MAIHDA
- Conceptual and practical challenges with MAIHDA
- Extensions of MAIHDA
Format
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 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.
Materials
Participants will be emailed in advance with comprehensive PDF copies of the lecture slides together with annotated syntax files and datasets for R and Stata.
Pre-requisites
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 R and Stata.
We assume you are already users of R or Stata and so have these software already installed and know the basics.
Participants might wish to have a look at our MAIHDA tutorial paper prior to attending, although it is not required: Evans, Leckie, Subramanian, Bell, Merlo (2024) A tutorial for conducting intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA). SSM-Population Health, online.
Practical information
The course will be held in-person at the School of Education, University of Bristol. Please bring your own laptop to work on, with software installed and updated. Catering (hot drinks and lunch) will be provided.
Timings
The course starts at 10:00 and ends at 17:00, with a one-hour break for lunch from 13:00 to 14:00.
Fees
The course is free – no payment is required.
Applications
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 4th May 2025.
Applications will be processed on a rolling basis, once a week, until the application deadline. There are 24 places available – once we reach capacity, we will create a waiting list.
You will receive a confirmation of acceptance email if you are successful in gaining a place on the course.
If you have any queries, please email info-cmm@bristol.ac.uk.
Please be aware that this course is now twice over-subscribed and any applications will automatically be added to the waiting list
Terms and conditions
Note that it is the participant’s responsibility to ensure that their laptop and their choice of 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 on the day.