National Centre for Research Methods

‘Dad Data’ is a one-day course designed to introduce participants to existing quantitative and qualitative data about UK fathers, which can be accessed from data archives for secondary analysis.

This data - that tells us about men in their roles as fathers and male caregivers (and their impacts) – can, and should, be used in secondary analysis to address research questions about children, young people, interparental relationships, families, work, caring, gender and other societal issues.

Although ‘dad data’ is ready and waiting to be analysed, researchers may not be aware of its existence or know how to make use of it for their own research interests. This means that the potential of ‘seeing’ fathers in data and analysing societal concerns through the lens of fatherhood is yet to be fully realised, with subsequent policy and practice impacts missed.

Participants will be introduced to the creative ways in which researchers might ‘see’ and research fathers in data, have opportunities to explore the relevance of ‘dad data’ for their own work, and to identify new research questions and future directions. 

In this online course, we outline a comprehensive framework for understanding the trade-offs involved in designing and remodelling social surveys. Our framework is rooted in the Total Survey Error and Total Survey Quality approaches, balancing the need to reduce sources of error against the constraints of a project, time and costs. Through real-life examples and case studies, we discuss the advantages and disadvantages of different research designs, with a focus on mixed-mode surveys, and the key steps involved in making informed decisions and remodelling surveys.

This course is for anyone involved in the design of survey research and will be particularly relevant for those who are running an existing survey and exploring alternative modes of data collection.

This course will introduce participants to arts in health as a field of study. This will be used to frame co-production in social health research. It will provide a background into the theories behind co-production as a research method, which sits in the anthropological field by its immersive nature. This pedagogy will provide a background to social policy and menstrual health, taking a closer look at menstrual artivism artefacts as a form of qualitative data.

This in-person course will provide participants with an understanding of the complex intervention research process. Presentations and activities will relate to the main concepts of developing/identifying and evaluating complex interventions and support participants to apply the principles to their own research. It will focus on the overarching considerations required to develop complex intervention research projects, rather than the details of study design, and enable researchers to develop and conduct research that will provide the most useful evidence for decision making. The course will be structured around the MRC/NIHR Framework for Developing and Evaluating Complex Interventions. There will be a mix of lectures and small group activities to put learning into practice. 

It is for anyone interested in developing, evaluating and implementing interventions with the intention of positive health and/or social change. This could be academic or other researchers, practitioners, or others interested in implementing the best process for their intervention development or evaluation. Participants should have some familiarity with the framework for developing and evaluating interventions, and some experience of working with complex interventions. 

The course covers: 

• Introduction to using the Framework
• Developing and identifying interventions
• Feasibility research
• Evaluation research
• Implementation & round up

In this one-day online training workshop you will be introduced to four qualitative research methods to better understand diverse lives - Photo Go-Alongs, Collage, Life History Interviews and Participant Packs. When researching social groups, researchers may focus on categories such as age, gender, sexuality and so on. These categories can turn catch-all terms into catch-all agendas. Treating groups of people with one shared characteristic as homogenous risks a cookie-cutter approach which overlooks diverse lives and needs. Given the complexity of what it means to be a person, a one-size fits all approach to engagement cannot suffice. The methods introduced in this training workshop are beneficial in exploring diverse lives and can be used when researching with any group. 

The session is aimed at PhD students and academics of all career stages across the UK who want to better understand: 

• The specific place-based needs of people 
• The everyday practices of people
• The world from participants’ perspectives
• How to work with people in an inclusive and accessible way

This online training workshop will be structured as follows:  

• Introductions
• Origins and Approach 
• Methods deep dive: 
• Photo Go-Alongs
• Participant packs
• Collage 
• Life Histories 
• Workshops 
• Learnings and close 

By the end of the course participants will:

• Be able to think critically about how creative, participatory methods might be incorporated into their research and/ or teaching. 
• Have broadened their understanding of research methods from tools of data collection to techniques for capacity building.
• Have workshopped four qualitative methods for creatively engaging with people (Photo Go-Alongs, Collage, Life Histories and Participant packs).

This online training workshop will take place over the course of 1 day on Wednesday 11th December between 10:00 and 16:00, with 1 hour for lunch between 12:30 and 13:30. 

This course is run as a collaboration between the National Centre for Research Methods and Administrative Data Research UK and is part of a series on short courses on administrative data.

The aim of the course is to provide an introduction to the Growing Up in England (GUiE) dataset. GUiE is a flagship ADR dataset and provides a link between 2011 Census data and longitudinal administrative data from the education and children’s social care systems.

The course provides an introduction and overview of GUiE including: 

• The different component datasets that are brought together in GUiE

• Waves and linkage methods

• Coverage, years and gaps

• Strengths and limitations

• Exemplar analysis

• The application process, documentation and support

By the end of the course participants will:

• Be familiar with the structure of GUiE
• Understand the content, coverage and years of the GUiE Waves 1-3 data
• Be aware of the strengths and limitations of the data available
• Be aware of existing studies and analysis using GUiE
• Have knowledge of GUiE documentation 
• Understand the application process, conditions of use and where to go for further information and support

Knowledge of administrative data research datasets and SDC processes would be helpful but are not essential. This is an introductory course and prior knowledge of or experience using GUiE is not required. 

PLEASE NOTE THIS COURSE IS BEING TAUGHT OVER TWO MORNINGS (10:00-13:00) AND EQUATES TO ONE TEACHING DAY FOR PAYMENT PURPOSES.

This one-day online, interactive course will provide a practical introduction to qualitative longitudinal enquiry. The morning session will explore key design features of this methodology, including how to build time into a study, how to sample through time, how to generate temporal data, the ethics of longitudinal enquiry, and the potential to create real-time impact in policy processes. The afternoon session will focus on the intricate nature of QL analysis. The course will comprise two lectures and two interactive workshops (see below and attached programme for further details).

The course will be delivered by Bren Neale, a specialist in QL research and the author of two books on this methodology.

This practical, one-day hands-on course provides a guided introduction to the workflow in ArcGIS Online (AGOL) for uploading and sharing your spatial data. You will learn how to publish existing vector data to AGOL, create views, set sharing and group privileges, create a web map that drives data collection and forms the foundation to an Experience Builder web application. The course comprises hands-on exercises each introduced with a short presentation and a live demonstration.

The course covers: 

• An introduction to ArcGIS Online (AGOL).

• Sharing your vector data from ArcGIS Pro to AGOL.

• Controlling access (settings, groups and views).

• Create a web map from your shared data.

• Build a web map application in Experience Builder.

• Configure layers for data capture.

• Accessing data in AGOL directly within ArcGIS Pro.

By the end of the course participants will be able to:

• Prepare and upload vector data from desktop ArcGIS Pro to ArcGIS Online.
• Create views, groups and set access privileges for hosted feature layers.
• Create a web map, set layer symbology and configure pop-ups.
• Edit a layer and conduct data capture.
• Create an Experience Builder application from the web map.
• Access layers in AGOL directly within ArcGIS Pro for data analysis.

This course is intended for users of ESRI’s ArcGIS Pro software who wish to improve their technical knowledge and understanding in ArcGIS Online (AGOL), the cloud-based counterpart, to traditional desktop GIS. Delegates must be familiar with the basics of using ArcGIS Pro and spatial data, familiarity with AGOL is an advantage but not essential. Training will be run at our dedicated training suite located on the Highfield Campus, University of Southampton. Room 1065 in building 44 (Shackleton).  GeoData will provide access to ArcPro 3.x and ArcGIS organisational logins for the course duration.

This course will run from 09:30-17:00.

This course provides an introduction to National Pupil Database (NPD), an administrative data resource covering the education system in England.

The course covers:

• The population coverage of NPD
• The component modules of NPD and how they link together
• How to create a longitudinal picture of pupils’ lives in schools
• Key data cleaning routines
• Accessing NPD

By the end of the course participants will:

•  Be familiar with the structure of NPD
•  Understand the strengths and limitations of the data available
•  Know where to go to find more detailed information
•  Know how to apply for access

This course is suitable for anyone intending to undertake quantitative research on the school system in England. No prior knowledge of the NPD or statistical code is required to access the course.

To prevent obesity or smoking initiation among teenagers, who should be targeted in an intervention? How can we contain the spread of an infectious disease under limited resources? Who should be vaccinated first in order to be most effective during vaccination shortages? How can we dismantle a terrorist organization, a drug distribution network or disrupt the communication flow of a criminal gang?

Social network analysis offers the theoretical framework and the appropriate methodology to answer questions like these by focusing on the relationships between and among social entities. Unlike transitional research methods, we shift the object of study from the individual as the unit of analysis, to the social relations that connect these individuals. A network is therefore a structure composed of units and the relationships that connect them. Network analysis is about the position of these units, the overall structure and how these affect the flow of information.

This short online course provides an introduction to an existing data linkage between the Ministry of Justice and Department for Education, with a particular focus on the Police National Computer (PNC) and National Pupil Database (NPD). The course will include a mixture of lectures, interactive sessions, and practical exercises to put learning into practice.

The course covers: 

• Accessing the data share

• Overview of available data 

• Tips and considerations for data cleaning

• Successfully clearing outputs

• Case studies using the linked dataset

By the end of the course participants will:

• Know how to access the data share
• Be familiar with the content of the data
• Know how to navigate some data cleaning challenges
• Understand some strengths and limitations of the data
• Know how to create successful outputs for clearance

This course will suit anyone interested in conducting quantitative data analyses using linked education and crime data in England. This may include, but is not limited to, quantitative researchers in academic, government, or third sector settings. People at any stage in their research career would be welcome, but the course will likely most interest PhD students, early career researchers, and mid career researchers.  

No specialist prior knowledge of the NPD, PNC, or statistical software is needed to attend, but a basic knowledge of research design and quantitative data analysis would be beneficial.

No prior reading is required for this training, but applicants may wish to explore existing outputs arising from the NPD and PNC, such as:

• https://www.adruk.org/news-publications/publications-reports/moj-dfe-linked-dataset-feasibility-study-data-quality-report/
• https://www.gov.uk/government/publications/education-childrens-social-care-and-offending

THIS COURSE IS BEING TAUGHT OVER TWO MORNINGS AND EQUATES TO ONE TEACHING DAY FOR PAYMENT PURPOSES.

In this one-day online training workshop you will be introduced to a knowledge equity method, a qualitative method designed to better redress the power imbalances that are inherent in the majority of traditional and even some participatory academic research-knowledge production. Oftentimes, researchers may be entirely unaware of the power imbalances in which they are complicit in reproducing through their well-meaning, carefully and well considered research design plans.

This workshop first highlights an exploration of the inequities often found in mainstream research practices, hence why a knowledge equity method is required , taking the principles of knowledge equity and translating them into an applied method. The approach introduced in this training workshop is beneficial in understanding social relations and human behaviour offering a concrete way to avoid extractive and exploitative research. The approach considers different ways that knowledge equality can be used when working or researching with any group, especially those that have been traditionally underserved by society and policy.

The session is aimed at students, academics and any career stage researchers working in higher education and research institutions (and those organisations who support such activity) across the globe who want to better understand:

· Why traditional research can be harmful even when well meaning

· How you can strengthen your research practice to ensure potential harm is being minimized

· How to better engage with people invited to contribute to the research

· How to develop research designs working towards knowledge justice in a concrete way

This online training workshop will be structured as follows:  

• Introductions

• What is knowledge (in)equity and why do we need a knowledge equity method?  

• Methods deep dive: 

Principles of knowledge equity 

Online resource introduction

Applying knowledge equity as a method

Mapping ecologies of knowledge 

Reflective practice activities, including how to engage new and alternative ways of doing things

By the end of the course participants will:

• Be able to think critically and practically about how equitable research practices might be incorporated into projects and programmes. 
• Have broadened their understanding of participatory research methods from tools of data collection to embedded practices for meaningful engagement with people invited to contribute to the research throughout the research process.
• Have practically worked through four/five activities to begin applying a knowledge equity method 
• This online training workshop will take place over the course of 1 day on Monday 21^st October between 10:00 and 15:00, with 1 hour for lunch between 12:30 and 13:30. 

PLEASE NOTE THIS COURSE IS BEING RUN x3 to DIFFERENT AUDIENCES (21^st, 25^th  AND 28^th OCTOBER).  IF YOU ARE A STUDENT/ACADEMIC PLEASE REGISTER FOR THIS SESSION, IF YOU ARE A POLICYMAKER/CIVIL SERVANT, PLEASE REGISTER FOR THE COURSE RUNNING ON THE 25 OCTOBER. IF FROM NGO/CIVIL SOCIETY PLEASE REGISTER FOR THE COURSE RUNNING ON THE 28^th OCTOBER.

PAR aims to create a space for researcher and participants to co-produce knowledge and where relevant, action for change. PAR is considered as a research paradigm in itself, that embodies a particular set of concepts under which researchers operate (Minkler and Wallerstein 2008). These include respect for diversity, community strengths, reflection of cultural identities, power-sharing, and co-learning (Minkler 2000). In this session we will explore these principles, the cyclical approach to PAR and what this means in practice. Participants will be given the opportunity to learn terminology, understand participation in community engaged research, explore how power and positionality can change health outcomes in PAR, and learn about a variety of participatory methods and how they have been applied in different contexts, globally and within the UK. Participants will also be provided with the space to explore challenges they are facing in designing or implementing community engaged collaborative research within a discussion clinic forum. 

Random effects models are applied in a range of social science domains (e.g. education, health and economics). Across disciplines, however, they are often used for different purposes, with different specifications, or even with different terminologies.

These differences may well reflect genuine complexities and ambiguities that are associated with their implementation. This two-day course will focus on selected advanced issues in the application of random effects models in social research contexts. It is most suited to empirical social science researchers with some previous experience in using statistical models with random effects.

The participants will be invited to use their own computers in the virtual lab exercises. Participants should have at least one of the software packages Stata, SPSS and R installed on their computers in order to participate in the virtual labs. Example materials will be available in all three packages, although the largest volume of examples are available in Stata format. 
For webinar sessions: 

Required: Some previous knowledge and experience of using statistical models in the social sciences
Desirable: Some previous experience of implementing random effects models in applied research

Software requirements for participation in the virtual lab sessions: 

Required: Access to at least one software from Stata, SPSS or R. Use of a secure computer that will support downloading and storing data files. Previous experience of using ‘command syntax’ code in statistical software to analyse datasets.
Desirable: Access to more than one software from Stata, SPSS and R. Access to MLwiN. 

Course will be delivered online and course times are 10:00 – 16:00 each day 

Randomised controlled trials (RCTs) are heralded as the gold standard of research design in the social sciences. RCT principles are used in research at all levels of complexity from evaluating national social policies to experimenting with the impact of website designs (there often known as A/B testing). This course is for social researchers who have a firm grasp of the foundations of quantitative research methods (e.g., linear regression and confidence intervals) and would like to learn how to design and analyse randomised controlled trials. The course incorporates a blend of presentations and participatory sessions, using examples from the social sciences.

This online course is aimed at researchers who are interested in learning more about community-engaged and co-produced research methods to conduct collaborative research with community groups and organisations. The training is delivered by two researchers with over 10-years experience in community-engaged research both of whom are also currently engaged in community-based research and teaching.

Over two half-days we will focus on both why and how to co-produce research with communities drawing on resources from academic and community sources as well as a range of useful examples from across our work in academia and the third sector. The course will focus in on the practicalities of working with and training community research teams as part of collaborative projects and will include practical ‘how-to’ guidance for enabling community researcher training to serve as an important space for collaboration across research teams. 

We broadly consider what we mean by community research exploring the different contexts this work has developed out of. We reflect on ethics, thinking about how to approach this work and suggest areas to consider in advance. We then focus on the ‘doing’ of the work, sharing the pragmatics of how we approach this work from designing research projects, to training collaborators, co-designing questions, carrying out fieldwork, analysis and dissemination. 

The training is discursive and interactive and aims to support people new to this area of research by sharing examples of practice and resources to draw on as well as enabling those with more experience to build on their existing knowledge.

The course covers: 

Introduction to community research

• Introductions.
• Exploring the definitions and principles of community research, co-production, engaged and participatory research.
• Different approaches and perspectives to community research-looking across disciplines and sectors.
• The role and potential of Community Researchers.
• Motivations and values of community-based research 
• Ethical practice – adopting an ethic and care and managing ‘mess’.

Motivations and values

When and how to co-produce – methods of co-production

• Co-producing across the research cycle-pragmatics
• Bringing different forms of expertise together-the role of training. 
• Employing creative methods within community research 
• What does ‘good’ look like?

By the end of the course participants will:

• be able to situate coproduced community research within a diverse range of practice and traditions. 
• be able to reflect on, anticipate and manage some of the ethical issues that may arise during community-based research 
• be able to recognise when and how community-based research is appropriate. 
• be able to draw on a range of pragmatic ideas and resources to support the set-up delivery and dissemination of community-based research.
• be able to develop bespoke strategies to support community researchers within collaborative projects

This course is aimed at all researchers/project managers/public engagement professionals at any career stage interested in developing community based/co-produced/participatory research.  A basic working knowledge of zoom would be useful but a guide and support can be provided.

Preparatory Reading

Living Knowledge Report would be useful to review but no pre-reading is necessary. 

Creating Living Knowledge Report (2016)

RACE Charter (2024): RACE+Charter.pdf (squarespace.com)

Community Researchers and Community Researcher Training (2018)

Economists (and social scientists more broadly) are increasingly focusing on the measurement and causes of inequality in health. This reflects the concern that health inequality reflects social injustices, and it is also in response to the trend away from a narrow focus on income inequality to broader inequality in wellbeing analysis.

This three-day online course aims to postgraduate researchers and analysts interested in quantitative analysis of inequity and (socio-economic and regional) inequality in health and health care. This consists of lectures and practical sessions on measurement and interpretation of inequity and inequality in health and health care. Specifically, this course provides a gentle introduction to the concept of inequity, socio-economic inequality, and inequality of opportunity in health, i.e., the “egalitarian” framework that does not necessarily indicate equality of the distribution of outcomes per se but emphasises the role of individual responsibility in defining a “fair” distribution of health in the society.

Recent advances in the survey measurement of health, in the context of large-scale social science datasets, allow us to access and collect physical measurements and markers derived from biological samples, in addition to self-reported health assessments. Measurement error in self-reported health data (as well as potential measurement errors in “more objectively” measured nurse-collected indicators in social science surveys) may significantly affect and contaminate the measurement of socio-economic inequality in health research when relying on these health measures. We will draw conclusions on the potential implications of measurement error in self-reported and measured health indicators for research in inequalities in health. Additional sessions will also take place on specific topics in health inequalities such as: a) the social and economic factors which may drive the observed regional inequalities in health within and between countries with the presentation of international evidence and practical sessions, and b) the role of reforms in shaping socio-economic inequality in health and healthcare.

We will also provide a good set of practical sessions and illustrative examples on the measurement of inequality in health using subjective and more objectively measured health indicators.

The course covers:

•  A gentle introduction to inequity and socio-economic (and regional) inequality in health and health care
• A number of approaches (employed by economists, social scientists and bio-social researchers) on the measurement of socio-economic inequality in health and healthcare
• The concept of inequality of opportunity in health
• Measurement of inequality and inequality of opportunity in health
• Measurement error in self-reported (and measured) health data in social science surveys and its potential implications for the socio-economic inequality in health research.
• The social and economic factors which may drive the observed regional inequalities in health within and between countries.
• The role of reforms on shaping socio-economic inequality in health and healthcare.
• Practical sessions and illustrative examples on the measurement of health inequality, measurement error in health outcomes and the potential implications for existing research in health inequality. 

By the end of the course participants will:

• be able to understand several approaches (employed by economists, social scientists and bio-social researchers) on the measurement of inequity and socio-economic inequality in health and healthcare
• be comfortable in computing health inequality measures using Stata
• understand the concept of inequality of opportunity in health and its measurement via practical sessions in Stata
• have the theoretical and practical knowledge to undertake basic research into health inequalities.
• be familiar with measurement error in health data available at social science surveys and its potential implications for existing research in socio-economic health inequality. 

This course is aimed at Postgraduate researchers and analysts interested in the measurement of socio-economic inequality in health and health care, including (but not limited to): Academics, Government Researchers, Third sector organisations and (Health) Consultancy analysts. Participants will need intermediate knowledge of Stata.

Data and statistics form the basis of much political discussion about crime, provide the foundation for evidence-based research on justice interventions, and shape our understanding of possible biases in the justice system.
However, working with any social science data can be complex, and there are particular features of working with criminological data that can pose challenges for researchers.

Data and statistics form the basis of much political discussion about crime, provide the foundation for evidence-based research on justice interventions, and shape our understanding of possible biases in the justice system.
However, working with any social science data can be complex, and there are particular features of working with criminological data that can pose challenges for researchers.

This is a two-day course on statistical methods for meta-analysis using the package STATA. The first day gives an overview on traditional techniques used in meta-analysis. The second day present more recent state-of-the-art modelling including mixed Poisson and binomial regression. The teaching style of the course is a mix of lectures and practical work. 

The course covers: 

• Basic elements: Effect measures of interest; Mantel-Haenszel, case studies, continuous outcomes; graphical techniques, precalculated effect measures
• Heterogeneity: why is there heterogeneity, study as random effect, sub-group analysis, meta-regression
• Meta-analysis of rare events: what are the issues? Mantel-Haenszel estimation 
• Modelling approaches for rare meta-analysis: Poisson and binomial with fixed and random effects
• Meta-analysis for rare events: single- and double-zero studies and their effect
• Conditional logistic regression

By the end of the course participants will:

•  Be able to do a simple statistical meta-analysis using traditional techniques
•  Be able to do a more advanced model-based meta-analysis 
•  Know in which meta-analysis setting to apply the most appropriate statistical approach 

Preparatory Reading

Introduction to Meta-Analysis, second edition (authors: Michael Borenstein, Larry V Hedges, Julian P T Higgins and Hannah R Rothstein.

Knowledge in STATA is helpful but not an essential pre-requisite.

This course will take place at the University of Southampton from 9am to 5pm both days (please note refreshments will be provided but lunch will not).

Deliberative research is emerging as a critical method for exploring public attitudes particularly on social and policy problems that are contested, complex or uncertain.  More broadly deliberation - through methods such as Citizens assemblies and juries - is used in society as a way to engage citizens in policy decisions.

This live online course explores the principles, benefits and limitations of deliberative approaches to social research and engagement, with a particular focus on the challenges and opportunities of delivering these online. We cover a combination of theory and practical examples to consider both doing deliberative research and being a deliberative researcher.

It is suitable for those with existing experience of the theory and practice of qualitative research and aimed at those who have responsibility for designing, commissioning and overseeing the delivery of research projects. 

This course will be useful to you if:

• You want to expand the range of participative qualitative methods you use for research
• You want to learn more about the use of online approaches to social research
• You have used deliberative research approaches in face to face studies and want to consider how to bring it online
• You want to know more about deliberation in general and how to deliver deliberative processes