Themes
Our themes reflect the range of approaches and advanced methods employed across the institute in social and political research.
This group focuses on the development and application of statistical models to investigate substantive phenomena in the social sciences and beyond.
We are also interested in the continuing software developments for fitting statistical models.
As well as doing research that involves statistical models, we also run training courses and seminars to explain how the latest software developments allow us to fit statistical models to answer substantive research questions. These include advice on the preparation of data and the interpretation of results.
We are primarily based in Social Statistics, but we are also involved in interdisciplinary collaboration at the University of Manchester, as well as working with colleagues elsewhere in the UK, and overseas.
Recent research topics include the development and application of the following models:
- Multilevel (hierarchical) Models for analysing data that have hierarchical, clustered, or cross-classified structure.
- Bayesian hierarchical models for integrating traditional and new forms of data.
- Longitudinal Models.
- Models for Social Networks, such as Exponential Random Graph Models (ERGMs) for the analysis of social network structures.
- Structural Equation Models.
Theme Coordinator
This research group focuses on developing a research agenda around data, skills, and training, with a particular emphasis on statistical and data literacy.
The group covers the following activities, all based at the Cathie Marsh Institute for Social Research (CMI): CMI short courses, methods@manchester, National Centre for Research Methods, Q-Step, and UK Data Service user support and training.
Events and activities
Selected projects and grants
UK Data Service
The UK Data Service is a comprehensive resource funded by the ESRC to support researchers, teachers and policymakers who depend on high-quality social and economic data.
Here you will find a single point of access to a wide range of secondary data including large-scale government surveys, international macro data, business microdata, qualitative studies and census data from 1971 to 2011.
All are backed with extensive support, training and guidance to meet the needs of data users, owners and creators.
The CMI team provide expertise on government surveys, census microdata, and user support and training.
Q-Step
Q-Step is a £19.5 million programme designed to promote a step-change in quantitative social science training.
The Manchester Q-Step Centre is undertaking a range of activities to support the development of quantitative skills in our undergraduate social science courses.
These include a range of new courses, dissertation support and a nationally recognised programme of summer internships.
We place up to 50 students a year with a wide range of organisations, working on projects designed to develop and practice quantitative data skills in a real research setting.
National Centre for Research Methods (NCRM)
In 2004 the Economic and Social Research Council (ESRC) set up the National Centre for Research Methods (NCRM) at the University of Southampton.
NCRM was tasked to increase the quality and range of methodological approaches used by UK social scientists through a programme of training and capacity building, and with driving forward methodological development and innovation through its research programme.
In October 2014 the NCRM formed a partnership between The University of Edinburgh and The University of Manchester, both of which have international reputations in methodological research and training in the social sciences.
methods@manchester
methods@manchester is an initiative that highlights Manchester's strength in research methods in the social sciences.
We run ‘What is..?’ and ‘How to…?' events, a postgraduate Methods Fair every November, and a Summer School.
We are increasingly engaging with external organisations who undertake data analysis.
Theme Coordinator
Coming soon
Social Data Science is a newly formed research group focusing on the empirical, methodological, and technical dimensions of large-scale data in social contexts.
The group brings together researchers with quantitative and qualitative backgrounds from different fields to tackle emerging challenges from using unstructured heterogeneous data in social science research. Our research agenda includes but is not limited to:
- deliver methodological innovations driven by social theory;
- provide fresh insights into new and existing questions about human and social behaviour using e.g. digital trace data;
- integrate tools from data science, e.g. machine learning, into social science research.
Theme Coordinator
This group aims to provide a focal point for researchers in the School of Social Sciences on the development and application of survey methodology and the analysis of complex survey data.
More specifically, the focus is on topics in survey methods and statistics, including questionnaire design, design of data collection (including longitudinal data collection), measurement error, interviewer effects, compensating for non-response, small area estimation, non-probability sampling, data linkage, and integration, confidentiality, and privacy.