The Centre for Multilevel Modelling (CMM) is a research centre based at the University of Bristol. Our researchers are drawn from the School of Education and School of Geographical Sciences. We collaborate with a range of researchers working with multilevel models.
Multilevel Modelling is one of the basic techniques used in quantitative social science research for modelling data with complex hierarchical structures. The Multilevel Modelling research theme focuses on producing new statistical methods for tackling research questions, developing new software for implementing this methodology and disseminating these techniques to the national and international social science community.
We develop new statistical methodology, implemented in software to address unsolved issues in quantitative modelling of social processes.
Longitudinal Effects, Multilevel Modelling and Applications is a node of the third phase of the ESRC National Centre for Research Methods (NCRM). More information
Interrelationships between housing transitions and fertility in Britain and Australia
The principal aim of this project is to examine the extent to which housing transitions and residential location choice are influenced by fertility outcomes such as the birth of a(nother) child or a child reaching primary or secondary school age, allowing for the effects of other social processes such as union formation and dissolution and employment changes. More information
Multilevel Modelling Government's School Performance Measures, 'Floor Standards' Target & 'Narrowing the Gap' Priority
Each year, the Government publishes school performance tables that report the achievement and progress of pupils in English secondary schools. In the 2011 tables, the Government introduced a number of changes. These changes have important implications and it is therefore imperative that they are critically reviewed and that innovative techniques are developed and applied to explore potential improvements to the accuracy, usefulness and communication of school performance tables.
This grant will do this by pursuing a programme of methodological and substantive research using multilevel modelling, and based on secondary analyses of the Government’s highly detailed pupil and school level performance data which underlie their tables. More information
Use of interactive electronic-books in teaching and application of modern quantitative methods in the social science
The aims of this project are to provide computer-assisted support to increase the skills and understanding of quantitative principles and techniques of researchers in UK social science, and to create innovative tools for reproducible research. More information
Gallery of Multilevel Papers
Videos and voice-over presentations
Advanced quantitative methods in social science and health
The Advanced Quantitative Methods (AQM) pathway of the SWDTC offers ESRC +3 postgraduate research training in the application of advanced quantitative methods in the social sciences and health. More information
The Centre for Multilevel Modelling's own software enables quantitative social science researchers to become effective multilevel modelling practitioners.
- Purchase MLwiN
- Upgrade to latest version
- Download for free if you are a UK academic
- Software help: MLwiN FAQs, MLwiN user forum.
Stat-JR is a software environment for promoting interactive complex statistical modelling. It is designed to make it easy to analyse large and/or complex datasets, learn statistical methods and develop new statistical methodologies. It also provides access to imputation methods for handling multilevel missing data via downloadable templates.
- Realcom (Developing multilevel models for REAListically COMplex social science data). Realcom-Impute Realcom macros with interface for handling missing data.
- MLPowSim Application for performing sample size/power calculations in multilevel models via simulation.
- R2MLwiN is an R command interface to the MLwiN multilevel modelling software package, allowing users to fit multilevel models using MLwiN from within the R environment.
- runmlwin Stata command to fit multilevel models in MLwiN from within Stata.
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