Groups

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

• NCRM
• Short courses (CMI)
• UK Data Service

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.

Leads

• Mark Brown
• Vanessa Higgins

This research group brings together a range of interests in these fields, incorporating work from political science, sociology, demography/human geography, and social statistics.

The core of the work is funded through the ESRC Centre on Dynamics of Ethnicity (CoDE), but also through several Hallsworth, British Academy, and ESRC Future Leaders Fellowships and associated funding, and research emerging from other funded activities.

Selected projects

The Centre on Dynamics of Ethnicity (CoDE)

The Centre on Dynamics of Ethnicity (CoDE) is a four-year interdisciplinary programme of research concerned with understanding changing ethnic inequalities and identities.

CoDE utilises a variety of research techniques and tools to ensure that the potential economic and social benefits of our research are realised.

Our focus is on the changes within ethnic groups (their internal structures and formulations of identities) and their external relationships and position in British society.

The Social Complexities of Immigration and Diversity

The SCID project will integrate two very different disciplines, social science and complexity science, to gain a new understanding of the complex, social issues surrounding immigration.

It will do this by building a series of computer simulation models of these social processes.

One could think of these as serious versions of the Sims computer games, programmes that track the social interactions between many individuals.

Such simulations allow ‘what if’ experiments to be performed so that a deeper understanding of the possible outcomes for society as a whole can be established based on the interactions of many individuals.

British Religion in Numbers (BRIN)

There is much public discussion of such issues as how secular Britain is, how religiously diverse, whether people see political and religious identities as conflicting, and how polarised religious views are.

Religious data is also important for public decision-making – by local authorities, central government and other public bodies.

There is a great deal of historical and contemporary data available, but it has hitherto been scattered, or difficult to access by many researchers.

BRIN aims to enable access to religious data, by researchers of all backgrounds.

Lead

• Bridget Byrne

Lifelong Health amalgamates previous research groups (Health Inequalities Research Group, Manchester Well-being Research Group) and works closely with allied Cathie Marsh Institute for Social Research (CMI)-based research projects (e.g. MICRA, fRaill).

We aim to foster world-class research into the social causes, correlates, and consequences of variation in health and well-being.

As well as established researchers, we specifically aim to bring together the new generation of doctoral researchers, regardless of disciplinary boundaries.

Selected projects

English Longitudinal Study of Ageing

The primary objective of the English Longitudinal Study of Ageing (ELSA) is to collect longitudinal multidisciplinary data from a representative sample of the English population aged 50 and older.

We collect both objective and subjective data relating to health and disability, biological markers of disease, economic circumstance, social participation, networks, and well-being.

Leads

• Bram Vanhoutte

The interdisciplinary Privacy, Data Protection and Trust (PDPT) group comprises academics working in statistics, social science, social policy, computer science, and law.

This longstanding research group continues to deliver highly specialised consultancy and research.

PDPT's overarching research goal is to investigate the confidentiality and privacy issues that arise from the collection, dissemination, and analysis of data.

The research has many facets, ranging from ethics to mathematics, from social to computer science.

Selected projects

UK Anonymisation Network (UKAN)

The UK Anonymisation Network (UKAN) has been set up as a means of establishing best practice in anonymisation and offers practical advice and information to anyone who handles personal data and needs to share it.

UKAN aims to maximise the value of data, minimise the risks to privacy and preserve public confidence by collating best practice in anonymisation from a wide range of experienced practitioners.

Leads

• Emma Barrett
• Mark Elliot

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.

Social Mobility and Labour Markets aims to promote research on social mobility and labour, gender aspects of labour and mobility research, and the integration of PhD and early career researchers in the Cathie Marsh Institute for Social Research (CMI) and their schools.

At present, we have approximately 40 people aligned with our group. This includes representation from different departments in Sociology at the University and representation from PhD researchers at The University of Manchester.

Leads

• Yaojun Li
• Wendy Olsen

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.

Leads

• Arkadiusz (Arek) Wiśniowski

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.  

Leads

• Natalie Shlomo
• Alexandru Cernat

Current PhD students

• Fiona Pashazadeh - Addressing non-response in biological data collection using nurse effects and survey paradata.
• Hafsteinn Birgir Einarsson - Improving response rates and data quality through optimised survey invitation letters.
• Raul Ungureanu - Understanding comparisons between surveys and social media data.
• Sofia Eleftheriadou - Collaboration problem solving and science teaching and learning.
• Zeming Chen - Using proactive approaches in preventing web survey break-offs.