National Centre for Research Methods

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.

In this online course, run over two mornings, we will show you how to prepare and conduct spatial analysis on a variety of spatial data in R, including a range of spatial overlays and data processing techniques. We will also cover how to use GeoDa to perform exploratory spatial data analysis, including making use of linked displays and measures of spatial autocorrelation and clustering.

The course covers: 

• Understanding and being able to interpret Spatial Autocorrelation measure Moran's I
• Understanding Local Indicators of Spatial Association statistic
• Perform Spatial Decision Making in R
• Perform Point in Polygon analysis using different approaches
• Be aware of the advantages and disadvantages of using point based or polygon based data
• Using buffers as a part of spatial decision making

By the end of the course participants will:

•  Be aware of some spatial statistics concepts and be able to apply them to their own data using GeoDa
•  Be able to perform spatial decision making 
•  Understand the limitations and benefits of working with data in this way

This course is aimed as PhD students, post-docs and lecturers who have some existing knowledge of using R as a GIS and want to develop their knowledge of spatial stats and spatial decision making in R. Some prior knowledge of both R and GIS is required. It is also appropriate for those in public sector and industry who wish to gain similar skills. 

Students will be using R, RStudio and GeoDa. 

Students need to have completed my Introduction to Spatial Data and Using R as a GIS (https://www.ncrm.ac.uk/training/show.php?article=13142) course, or have equivalent experience. This includes:

Using R to import, manage and process spatial data

Design and creation of choropleth maps

Use of scripts in R

Working with loops in R to create multiple maps

For more information, please look at the link above or contact X. 

Students will need R (v > 4.0), and the sf, tmap, dplyr libraries. They will also need RStudio (v > 2023.01 or greater)

No prior knowledge of GeoDa is needed. It can be downloaded following the instructions at https://nickbearman.github.io/installing-software/geoda. Version 1.20 or greater is required. 

THIS COURSE WILL RUN OVER TWO MORNINGS (10AM TO 1PM) AND EQUATES TO ONE TEACHING DAY FOR PAYMENT PURPOSES.

This in-person course will introduce the analysis of individual-level outcomes for individuals that are connected through links in a social network. We will cover the basic statistical issues associated with analysing inter-dependent outcomes and then study models that specialise in inferring so-called social influence in cross-sectional network data. We will have a particular focus on a class of models for binary outcome variables called the auto-logistic actor attribute models (ALAAMs). Emphasis will be placed on practical hands-on exercises of real datasets in R. The course will run lunch-to-lunch over two days. The first afternoon providing the necessary background and provide the participants with the skills of applying and interpreting basic models. The second morning will present more advanced topics and deeper insight into estimation and interpretation issues.

• The aim of this two-day online training course is to introduce participants to the practice and ethics of ethnographic research. Through a mix of plenary sessions, group and independent work, participants will learn the basic principles of participant observation and research design, as well as the foundations of ethical ethnographic research. The course will also examine the ways in which other qualitative and creative methods of data collection may be productively integrated in ethnographic research.

  The course covers:

  • Research design

  • Qualitative methods in ethnographic research

  • Access and power

  • Research ethics in participant observation

  By the end of the course participants will:

  • Understand the epistemological foundations of ethnographic research

  • Have a solid understanding of ethnographic research in action

  • Be able to design and conduct research integrating qualitative and ethnographic research methods

  • Be able to conduct ethical ethnographic research

  The course is suitable for any professional researchers interested in learning more about using ethnographic methods – whether within or outside academia (private sector, government researchers, etc.).

  The course is likewise suitable for postgraduate students in any social science (human geography, sociology, business school, political sciences, area studies, education, etc.) with prior knowledge of any qualitative research methods, but not necessarily of ethnography.

  Some prior training in qualitative research methods, broadly defined – regardless of whether that includes ethnographic methods specifically.

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.

Data visualisation is one of the most important steps in any analysis journey. Visualisations allow us to explore our data, identify errors and outliers, generate hypotheses about possible relationships between variables, and communicate results clearly and efficiently. ggplot2 is a powerful R package that was designed to create publication-quality graphics in seconds. The joy of ggplot2 is its flexibility: graphs are built in layers which can be easily customised, ensuring novel plots to fit almost any situation.

 This online course will introduce the ggplot2 package and its underlying grammar of graphics. Participants will understand how to choose the most appropriate type of visualisation, based on the type and number of variables, and the intention of the plot. We will then build visualisations, layer by customisable layer, to transform simple plots into beautiful, informative graphics.

 The course covers:

• How to load, tidy, and prepare data for visualisation
• Introduction to ggplot2: how to produce a simple graph
• Enhance visualisations by customising layers: scales, themes, and annotations
• Faceting: multiple visualisations in one place
• Creating personalised colour palettes and themes for consistent visualisations

 By the end of the course participants will:

• Create compelling, clear data visualisations using the ggplot2 package
• Be able to customise graphs using scale and theme functions
• Know how to add annotations to graphs to make them as clear as possible
• Know when to facet graphs to show multiple plots on the same graph
• Save personalised colour palettes and theme functions to ensure visualisations are consistent

This course is open to anyone that would like to level up their data visualisation using the ggplot2 package. This could include PhD students, academics, government or other public sector analysts, etc. from any discipline.  Participants are expected to have some experience of loading and tidying data in RStudio using Tidyverse packages.

Participants will need R and RStudio installed on their computer. They will need to check that they are able to install packages from the online R repository (this is usually not an issue but some departments with secure data may have issues if they require an administrator password to install things to their machine). For this, participants can run the following code which will install and load the package we are using to their computer:

install.packages("tidyverse")

library(tidyverse)

This course will run from 10am to 4pm on Wednesday 27 November 2024

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

The course will be delivered through a mixture of taught sessions and practical exercises, and will be conducted online over one full day.
The course will cover the following topics:

• The importance of ethics in social research, and key ethical principles.
• Ethical considerations across the lifecycle of social research projects: at the design, recruitment, data collection, analysis and reporting stages.
• Risks to researcher safety and wellbeing.
• Practical considerations when providing ethics guidance.
• Practical considerations when making decisions to disclose confidential information.
   

By the end of the course participants will meet the following learning objectives: 

• Be able to identify and manage potential ethical issues and risks to potential participants and groups to which they belong at the research design and recruitment stages.
• Be able to identify and manage potential ethical issues and risks to participants at the data collection, analysis and reporting stages.
• Be able to identify and manage potential risks to researchers throughout the stages of primary research projects.
• Have gained experience of scrutinising ethics in social research projects.
• Have gained experience of considering when to disclose confidential information, and why.

This course will introduce participants to contemporary practice in ethnographic filmmaking, as well as the ethics, and practicalities that inform this diverse field of research practice.

It is aimed at beginners who are interested in incorporating the method into their social research but have no (or little) prior experience of filmmaking.

Course Timings: 10:00 – 17:00 

As part of pre-course joining instructions, we ask that delegates have watched a film.  

The links to view a film will be shared in the pre course joining instructions issued ONE week prior to the course date. 

All are available online, behind a paywall with the fee of approx £5.00 being applicable. Many universities subscribe to Kanopy, please check your institutional access.

Course Contents:

• Contemporary and experimental practice in the interdisciplinary field of ethnographic filmmaking;
• Critical history of the genre;
• Ethics of representation;
• Watching and decoding ethnographic films;
• Basic first steps for shooting a film;
• Important considerations for starting an ethnographic filmmaking project.

By the end of this workshop you will:

• Be able to think critically about the history of ethnographic filmmaking and how their practice can respond to this;
• Understand the core characteristics of contemporary ethnographic filmmaking – across the globe, and across genres;
• Have experience of watching and critiquing an ethnographic film;
• Be confident to start the process of shooting and editing an ethnographic film.

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 one day 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 online workshop aims to give participants a range of practical approaches they can adopt when writing about methodology in the social sciences. Using a range of exercises throughout, the course focuses on 20 or so writing strategies and thought experiments designed to provide more clarity and power to the often-difficult challenge of writing about methods. The course also looks at common mistakes and how to avoid them when writing about methods. The focus throughout is on building confidence and increasing our repertoire of writing strategies and skills.

 The course covers:

• A range of practical writing strategies for handling methodology
• The challenges of writing a PhD methodology chapter or a methods section in a research paper
• Writing for qualitative and quantitative research approaches
• Understanding different audiences and the needs of different academic markets

 By the end of the course participants will:

• Better understand who and what ‘methodology writing’ is for
• Know the differences and similarities between PhD methods chapters, research paper methods sections and methods books
• Understand and reflect on 21 principles (or starting points) of best practice in methodology writing
• Focus writing on audience needs and expectations
• Be aware of common mistakes and misunderstandings and so avoid them
• Reflect on the relationship between methodology writing and other parts of your manuscript
• To develop learning and best practice through exercises and examples

Target Audience:

PhD students, post-docs and junior researchers in the social sciences working on their doctoral theses or supervising doctoral students.

This online workshop will introduce Institutional Ethnography (IE), an interdisciplinary feminist approach to social research that focuses on how texts and language organise our everyday lives. IE is not just a methodology, but an entire approach to research with a specific ontology of how the social world works and the organising role of texts and language. In IE, the researcher ‘takes sides’ using a specific version of standpoint to explore how institutions work in practice rooted in peoples’ experiences. This often involves researching as, with, or alongside marginalised groups and making visible how institutions exclude or make invisible certain groups of people and experiences. 

The overall aim of the workshop is to provide attendees with a comprehensive overview of institutional ethnography as an approach and the opportunity to translate their own research ideas and projects into an IE research proposal and do a small piece of text-focused analysis. This hands-on workshop is suitable for students, academics, and anyone else interested in feminist methodologies, text and discourse analysis, and institutional or organisational ethnographies. No prior training in, or knowledge of, IE is required. 

The course covers: 

• An overview of Institutional Ethnography and the work of feminist sociologist, Dorothy Smith, who developed Institutional Ethnography 

• Case studies of Institutional Ethnography research projects to show how it works in practice in different disciplines

• How to translate your research into an Institutional Ethnography project using a research proposal framework

• Practical explanation of how to do text and discourse analysis within Institutional Ethnography through a short text analysis activity 

By the end of the course participants will:

• understand of the origin and development of Institutional Ethnography

• know how to use Institutional Ethnography to analyse texts, processes, and discourses

• have an outline of how their research ideas could become an Institutional Ethnography project 

This course is aimed at academics, students, any other qualitative researchers, including policymakers, organisers, and activists interested in analysing organisational processes.  Participants must have at least some experience in qualitative research methods, but no experience of Institutional Ethnography is required.

Preparatory Reading

Required:

• 1 hour lecture by Dorothy Smith summarising Institutional Ethnography - https://www.youtube.com/watch?v=1RI2KEy9NDw
• Murray, Ó.M., 2020. Text, Process, Discourse: Doing feminist text analysis in institutional ethnography, Available at: https://doi.org/10.1080/13645579.2020.1839162

Desirable:

• Earles, J., & Crawley, S. L. 2020. Institutional ethnography. In P. Atkinson, S. Delamont, A. Cernat, J. W. Sakshaug, & R. A. Williams (Eds.), Foundation: SAGE research methods. Retrieved July 17, 2020, from: http://dx.doi.org/10.4135/9781526421036759274
• Smith, D.E. & Griffith, A.I., 2022. Simply Institutional Ethnography: Creating a Sociology for People. Toronto: University of Toronto Press.

PLEASE NOTE THIS COURSE IS TAKING PLACE AT

UNIVERSITY COLLEGE LONDON

This short course is designed to give participants a practical introduction to data linkage and is aimed at both analysts intending to link data themselves and researchers who want to understand more about the linkage process and its implications for analysis of linked data—particularly the implications of linkage error. Day 1 will focus on the methods and practicalities of data linkage (including deterministic and probabilistic approaches) using worked examples. Day 2 will focus more on analysis of linked data, including concepts of linkage error, how to assess linkage quality and how to account for the resulting bias and uncertainty in analysis of linked data. Examples will be drawn predominantly from health data, but the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice.

The course covers:

• Overview of data linkage (data linkage systems, benefits of data linkage, types of projects)
• Overview of linkage methods (deterministic and probabilistic, privacy-preserving)
• The linkage process (data preparation, blocking, classification)
• Classifying linkage designs
• Evaluating linkage quality and bias (types of error, analysis of linked data)
• Reporting analysis of linked data
• Practical sessions (no coding required; see below)

By the end of the course participants will:

• Understand the background and theory of data linkage methods
• Perform deterministic and probabilistic linkage
• Evaluate the success of data linkage
• Appropriately report analysis based on linked data

The course is aimed at analysts and researchers who need to gain an understanding of data linkage techniques and of how to analyse linked data. The course provides an introduction to data linkage theory and methods for those who might be implementing data linkage or using linked data in their own work. Participants may be academic researchers in the social and health sciences or may work in government, survey agencies, official statistics, for charities or the private sector. The course does not assume any prior knowledge of data linkage. Some experience of using Excel or other software will be useful for the practical sessions.

Preparatory Reading

Recommended (not required):

· Doidge JC, Christen P and Harron K (2020). Quality assessment in data linkage. In: Joined up data in government: the future of data linking methods. https://www.gov.uk/government/publications/joined-up-data-in-government-the-future-of-data-linking-methods/quality-assessment-in-data-linkage

· Harron K, Doidge JC & Goldstein H (2020) Assessing data linkage quality in cohort studies, Annals of Human Biology, 47:2, 218-226, DOI: 10.1080/03014460.2020.1742379

· Harron KL, Doidge JC, Knight HE, et al. A guide to evaluating linkage quality for the analysis of linked data. Int J Epidemiol. 2017;46(5):1699–1710. doi:10.1093/ije/dyx177

· Doidge JC, Harron K (2019). Reflections of modern methods: Linkage error bias. International Journal of Epidemiology. 48(6):2050-60. https://doi.org/10.1093/ije/dyz203

· Sayers A, Ben-Shlomo Y, Blom AW, Steele F. Probabilistic record linkage. Int J Epidemiol. 2016;45(3):954–964. doi:10.1093/ije/dyv322 · Doidge JC, Harron K. Demystifying probabilistic linkage: Common myths and misconceptions. Int J Popul Data Sci. 2018;3(1):410. doi:10.23889/ijpds.v3i1.410

Programme

Day 1

• Overview
• Deterministic linkage algorithms
• Linkage error
• Probabilistic linkage theory and practical demonstration
• Practical considerations (including variable selection, handling missing data and managing processing requirements)
• Overview of advanced topics including privacy preservation, string comparators and linkage of multiple files

Day 2

• Recap: Common myths and misconceptions about probabilistic linkage
• Linkage error bias
• Linkage quality assessment
• Handling linkage error in analysis
• Reporting studies of linked data
• Software demonstration: Splink – open-source toolkit for probabilistic record linkage and deduplication at scale

The online one day course (which will be taught over two mornings) will introduce you to various empirical, quantitative methods that can be used to estimate the impact of a specific policy intervention. These methods can be referred to as “programme evaluation”, “impact assessment”, “causal estimation” or “impact evaluation”. The course assumes basic statistical concepts (mean, median, correlation, expected value, statistical significance and confidence intervals), and algebra is optional. It does not teach participants how to implement any of these methods using statistical software.

 The course covers:

• The evaluation problem, and how randomized experiments solve the problem
• An intuitive explanation of the advantages and disadvantages of matching, including propensity score matching; quasi-experimental methods such as instrumental variables; and difference-in-differences
• It does not teach participants how to implement any of these methods using statistical software

 By the end of the course participants will:

• Be able to think about evaluation in terms of “counterfactuals” and “informative contrasts” (or comparisons)
• Be able to explain intuitively the conditions under which propensity score matching, instrumental variables and difference-in-differences are likely to produce unbiased estimates of the impact of an intervention
• Be able to assess whether an actual or proposed design for an impact evaluation is likely to give reliable results, given the nature of the policy under consideration

This course is aimed at Government researchers and analysts interested in quantitative methods for impact evaluation, Third sector researchers and analysts interested in quantitative methods for impact evaluation and PhD students and junior researchers.

Longitudinal data is essential in a number of research fields as it enables analysts to concurrently understand aggregate and individual level change in time, the occurrence of events and improves our understanding of causality in the social sciences. 

In this course, you will learn both how to clean longitudinal data as well as the main statistical models used to analyse it. The course will cover three fundamental frameworks for analysing longitudinal data: multilevel modelling, structural equation modelling and event history analysis. 

The course is organized as a mixture of lectures and hands-on practicals using real-world data. During the course, there will also be opportunities to discuss also how to apply these models in your own research.

Objectives:

• To gain competence in the concepts, designs and terms of longitudinal research;
• To be able to apply a range of different methods for longitudinal data analysis;  
• To have a general understanding of how each method represents different kinds of longitudinal processes;
• To be able to choose a design, a plausible model and an appropriate method of analysis for a range of research questions.

IMPORTANT: Please note that this course includes computer workshops. Before registering please check that you will be able to access the software noted below. Please bear in mind minimum system requirements to run software and administration restrictions imposed by your institution or employer with may block the installation of software.

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.

In this one day course (online over two mornings) we will explore how to use R to import, manage and process spatial data. We will also cover the process of making choropleth maps, as well as some basic spatial analysis. Finally, we will cover the use of loops to make multiple maps quickly and easily, one of the major benefits of using a scripting language to make maps, rather than traditional graphic point-and-click interface.

The course covers:

• Using R to import, manage and process spatial data
• Design and creation of choropleth maps
• Basic spatial analysis
• Working with loops in R to create multiple maps

 By the end of the course participants will:

• Use R to read in CSV data & spatial data
• Know how to plot spatial data using R
• Join spatial data to attribute data
• Customize colour and classification methods
• Understand how to use loops to make multiple maps
• Know how to reproject spatial data
• Be able to perform point in polygon operations
• Know how to write shapefiles

This course is ideal for anyone who wishes to use spatial data in their role. This includes government & other public sector researchers who have data with some spatial information (e.g. address, postcode, etc.) which they wish to show on a map. This course is also suitable for those who wish to have an overview of what spatial data can be used for. Although no previous experience of spatial data is required it would be beneficial (eg Google Maps).

This course will be taught over two mornings (10:00 – 13:00, including a mid morning break) and equates to one teaching day for payment purposes.

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 policymakers/civil servants and professionals working in government at any level and professionals working within government across the globe who want to better understand: 

• Why traditional policy research and consultation can be harmful even when well meaning 
• How you can strengthen your research and consultation practices to ensure potential harm is being minimized
• How to better engage with people invited to inform policy 
• How to develop research designs working towards non-extractive policymaking 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 Friday 25th 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 POLICYMAKER/CIVIL SERVANT PLEASE REGISTER FOR THIS SESSION. IF YOU ARE A STUDENT/ACADEMIC PLEASE REGISTER FOR THE COURSE RUNNING ON THE 21st OCTOBER. IF FROM NGO/CIVIL SOCIETY PLEASE REGISTER FOR THE COURSE RUNNING ON THE 28^th OCTOBER.

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 individuals working for NGOs and civil society working across the globe who want to better understand: 

• Why traditional research, consultation and project design can be harmful even when well meaning 
• How to you can strengthen your project planning, research, and consultation to ensure potential harm is being minimized
• How to better engage with people invited to inform campaigns, consultation, projects and research  
• How to develop research designs working towards non-extractive engagement 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 28th 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 FROM NGO/CIVIL SOCIETY PLEASE REGISTER FOR THIS SESSION. IF YOU ARE A STUDENT/ACADEMIC PLEASE REGISTER FOR THE COURSE RUNNING ON THE 21st OCTOBER. IF A POLICYMAKER/CIVIL SERVANT PLEASE REGISTER FOR THE COURSE RUNNING ON THE 25^th OCTOBER.

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.

Multilevel and longitudinal statistical models are increasingly common in social science research. Many researchers whose interests are substantive rather than methodological struggle to understand these techniques and they are disinclined to engage with research that employs these approaches.  

This workshop is designed for researchers who would like to learn about multilevel and longitudinal statistical models. 

This one day workshop will be orientated towards researchers who do not normally use statistical methods but would like to be introduced to multilevel and longitudinal statistical models. It will be ideal for busy researchers who do not have time to go on longer workshops or courses. It will also be a useful refresher course for researchers whose last encounter with statistics was during their undergraduate degree.

If you frequently skip over tables of statistical modelling results when reading journal articles, then you will benefit from attending this workshop.

The event is intended to be engaging and informative. 

Mathematical ability is not required.

Conceptual ideas relating to statistical modelling will be introduced at a level that, although technically elementary, shows how statistical ideas can address major social scientific issues. 
The workshop will also point to training resources where greater depth of technical competence can be acquired.

This course is also suitable for researchers who have attended the previous NCRM course Statistical Modelling for Qualitative Researchers.

Course Timings: 10:00 – 16:00

The NCRM Autumn School 2024 is an in-person, intensive training event that will focus on digital research methods. The three-day event will provide attendees with an advanced critical introduction to five foundational aspects of digital research methods by leading experts in the field.

These five aspects are:

1. Code and algorithms as research methods; 

2. Digital datasets, their affordances and limits; 

3. Complexity, collaboration and heuristics for digital research; 

4. Prompting and interaction with AI systems;

5.  Open-source investigations and the critical imagination.   

The event will follow an opening dialogue-based session that will preview and contextualise the sessions to come as well as connect attendees and presenters.

Who the event is suitable for

Combining overviews of the state-of-the-art, worked through examples of significant research and hands-on exercises with different aspects of the digital methods covered that will build progressively over the three days, these sessions will provide a critical grounding in digital research methods for all of those seeking to develop their work as digital researchers and the contributions they can make through it. As such, it will be of particular interest to postgraduate and early-career researchers seeking to enter the digital field but will also be of interest more broadly to all those seeking to understand the potential and the limits of digital methods too.

With presenters drawn from across the social sciences and arts and humanities whose expertise intersects with data science, computational methods, digital archivism and critical investigative approaches to research, the Autumn School foregrounds interdisciplinarity and attendees are welcomed from all disciplines, fields and backgrounds, including those based outside academic institutions. 

Aim of the event

It is a truism that we are all digital researchers now and there can be no question that the digital pervades contemporary research. Indeed, reflecting the extraordinarily rapid processes of ‘creative destruction’ that characterise innovation in the field of digital technology in which new digital services, tools and forms of data rise and fall in the space of a few years, as researchers we are all confronted with a bewildering swarm of new technical possibilities but with few resources at hand that situate these developments and guide us as to how we should take them up if at all.

In a context of this kind, it is very easy to fall back on endless narrowly technical ‘how to’ guides and associated technological fixes without posing critical conceptual and methodological questions as to why we should be pursuing particular avenues of digital inquiry and investigation in the first place.

The broad aim of this Autumn School is to provide researchers with resources that will enable them to step back from the constant disruptions of the digital, ask critical questions about where they want to get and what contributions they want to make through their research and, from there, develop their engagements with the digital.

While the Autumn School will introduce attendees to specific digital methods, tools and resources, that is not its primary focus. Rather, the focus is on helping attendees develop the kind of critical, creative and investigative mindset that will enable them to arrive at assessments of those methods, tools and resources for themselves and the uses to which they might usefully be put in the context of their research.

The complexity of the digital means we are pulled into collaborations with others at all turns through our engagements with it and this Autumn School will provide a means of negotiating the politics and practice of digital research in a clear-sighted, critical and, crucially, equitable way. 

Application process

Attendance to this course will be funded by University of Liverpool and NCRM. Successful candidates will need to secure travel and accommodation at their own expense for the three full days of the course. 

To apply for a place on this Autumn School, please download the application form using the link below and email it to: [email protected]

Deadline for the application is Friday, 6 September 2024 at 12:00.

This online course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when carrying out analyses and publishing results based on HES. The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data.

The course covers:

• HES data collection and coding
• HES data structure
• How to clean and manage HES data
• How to ensure anonymity and confidentiality
• How to carry out basic analyses using HES data
• Sources of variation in HES data
• How to apply for HES data

By the end of the course participants will:

• understand how and why HES data are collected
• become aware of the strength and weaknesses of using HES data for research
• know how to carry out basic cleaning, management and analysis tasks using HES data
• know how to ensure anonymity and confidentiality when using HES

The course is for researchers and data analysts in academia, government and private sector at all levels who are using or planning to use HES for their work.

There are no pre-requisites for the lectures. Computer practicals will involve analysis of simulated data therefore previous experience of programming in Stata, R or SAS will be helpful. 

In this two day course (which will be taught online over 4 mornings), you will learn what GIS is, how it works and how you can use it to create maps and perform spatial analysis. We assume no prior knowledge of GIS and you will learn how to get data into the GIS, how to produce maps using your own data and what you can and cannot do with spatial data. You will also learn how to work with a variety of different data sources and types (including XY coordinate data and address or postcode data) and using spatial overlays, point in polygon analysis and spatial joins.
The course covers:

• What is GIS and spatial data?
• How to classify data for a choropleth map
• How to create a publication ready map
• How to work with different data sources including XY coordinate and postcode data
• Using attribute and spatial joins
• Using spatial overlays and spatial analysis
• How to apply these skills to your own data

By the end of the course participants will:

• Be able to set up QGIS and add data
• Know how to classify data for a choropleth map
• Be able to join tabular data to spatial data
• Designing and producing a publication ready map in QGIS
• Understand how to import a range of data types into QGIS
• Be able to locate and open a range of GIS data sets
• Know how to apply GIS analysis tools including spatial overlays and point in polygon.
• Be confident at applying the skills to their own data

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. 

This two day in-person course will introduce participants to qualitative participatory action research (PAR) methodologies including photo elicitation, journaling, systems workshops and (online) walking interviews. It will differentiate participatory action research from co-production research in terms of (i) focus, (ii) methodology, (iii) power dynamics and (iv) outcomes. 

Participants will explore the principles of PAR, such as respect for diversity, community strengths, cultural identity reflection, power-sharing, and co-learning. The course will cover the cyclical approach to PAR and its practical applications, including ethical considerations and participatory research with various groups, such as children and young people.

It will delve the integration of lived experience representatives into study design from ideation to data collection, interpretation, iterative validation and inclusive findings dissemination. 

This course will also explore the co-analysis (collaborative interpretation) aspect of qualitative PAR and co-production methodologies. Co-analysis involves collaborative data analysis processes where researchers and participants work together to interpret different forms of data, ensuring that multiple perspectives are considered and that the findings are grounded in the lived experiences of participants.

Participants will learn various co-analysis techniques, including:

• Thematic Analysis: Collaboratively identifying and analysing patterns or themes within qualitative data.
• Framework Analysis: Using a structured approach to manage and analyse data through matrices.
• Participatory Coding: Engaging participants in the coding process to ensure their experiences and perspectives are accurately represented.

The course will emphasize the importance of reflexivity, transparency, and ethical considerations in co-analysis. Participants will explore how to facilitate effective co-analysis sessions, manage power dynamics, and ensure that the co-analysis process is inclusive and respectful of all voices.

Qualitative Diary Methods (QDMs) are increasingly recognised as a valuable and important method in social science research, due to concern across disciplines with an overreliance on cross-sectional research, a lack of focus on temporality, and the need to capture evolving processes and the daily dynamics of phenomena.

QDMs offer a range of innovative approaches and tools for social science researchers that enable us to capture and subsequently begin to understand, how phenomena are experienced in the moment, as well as how they evolve over time. However, they remain a methodological blindspot in much postgraduate research training.

This workshop will provide researchers with a new range of methods to add to their methodological toolkit, as well as support and guidance in managing some of the challenges associated with these methods, including insights into qualitative diary (longitudinal) analysis approaches.

In this live online course, learn about questionnaire design in the context of different modes of data collection. Explore question wording issues, the questionnaire as a whole and visual concerns when moving from interviewer-administered to web survey, when creating a web survey in general and when facing the questionnaire design challenges in creating mobile-friendly web surveys. Mirroring in-person training this will be an interactive course and will also have workshops throughout.

The course covers:

• The push towards mixed mode, web and mobile web surveys
• Questionnaire design revision - Getting started, trade-offs, general guidelines, beware of certain question formats
• Question design solutions for comprehension issues - Appendix for memory and sensitivity issues
• Don't rely on survey templates
• Mixing modes of data collection, some overall mode differences, mode effects by question content and format
• From interview survey to web survey
• Web survey questionnaire requirements and options, web surveys can include . . . but should we?, importance of visual layout, unexpected issues with HTML formats
• Push to web
• Questionnaires for mobile web surveys - earlier evidence, later findings, current thinking on making a questionnaire mobile-friendly

By the end of the course participants will:

• Have better knowledge about questionnaire-related mode differences and effects
• Have the skill to change an existing interviewer-administered questionnaire to a web survey
• Have the ability to create effective web survey questionnaires as well as mobile-friendly ones
• Have greater questionnaire design skills in general and the ability to critique existing survey templates

This course is for anyone involved in mixed-mode, web and/or mobile web surveys.  Participants need familiarity with surveys and questionnaire design.

Ethical research is better quality research. This online course (one day, taught over two mornings) is designed to raise your awareness of why and how you need to think and act ethically in practice throughout your research work. The current system of ethical review by committee can lead to the misleading sense of having ‘done ethics’. This course shows you how to conduct research which is truly ethical. It also provides the opportunity for discussion of your own ethical dilemmas, if you wish.

The course covers:

• Research ethics in context – ethical breaches past and present, ethics dumping, ethics activism
• Potential ethical pitfalls at each stage of the research process, from question setting to aftercare
• How to think and act ethically throughout research

By the end of the course participants will:

• Recognise the importance of context for ethical decision-making
• Understand why they need to think and act ethically throughout research work
• Be clearer about potential ethical pitfalls at different stages of the research process
• Know how to approach ethical thought and action at any point in their research

This course is aimed at Doctoral students, early career researchers (any discipline). Also practice-based/applied researchers. Possibly government researchers too, and independent researchers.

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)

This entry-to-intermediate course provides a thorough introduction to the idea, application, and key topics in structural equation modeling (SEM).

Broadly, SEM is a powerful family of methodological approaches that typically involves advanced and sensitive estimation of (a) variables’ measurement structure and (b) pseudo-causal mediated relationships among such variables.

SEM has now been widely used throughout the social sciences, and provides a flexible and intuitive means of answering complex research questions.

This one-day course will provide participants a working starting point to begin their journey towards understanding and running their own SEM analyses in 

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

This one day course will explore temporal and creative research methods. In particular the course focuses on qualitative longitudinal interviewing techniques and creative activities used in support of interviews and group workshops to encourage participants to think over extended time periods, and engage with materials to consider valuable aspects of their lives and places they live. 

This two day course will outline creative research methods and show you how to use them appropriately throughout the research process. The course assumes that you have a good working knowledge of conventional research methods, and builds on that knowledge by introducing arts-based methods, embodied methods, research using technology, multi-modal research, and transformative research frameworks such as participatory and activist research. Any or all of these techniques can be used alongside conventional research methods and are often particularly useful when addressing more complex research questions. You will have several opportunities to try applying these methods in practice. Attention will be paid to ethical issues throughout. The course will include plenty of practical advice and tips on using creative methods in research.

The course covers:

• Arts-based methods
• Embodied methods
• Research using technology
• Multi-modal research
• Transformative research frameworks

By the end of the course participants will:

• Have a good level of knowledge of creative research methods
• Understand how to use creative methods alongside conventional methods
• Understand when to use creative methods in research
• Have more resources to counter any opposition to the use of creative methods
• Know how creative methods can add value to funding bids

This course will be relevant for researchers from the third sector, public services (e.g. health, criminal justice, social care, education, local or national government), and those who work in independent research organisations or academia. It is an intermediate level course and attendees will need a good working knowledge of conventional research methods.

The course will run from 10.30-17.30 on Day One and  9:00-16:00 on Day Two.  Refreshments will be provided over the two days, however, lunch will not.  There are various places nearby to purchase something.

Preparatory Reading

Although not required participants may wish to purchase the book on which the course is based: Creative Research Methods: A Practical Guide (2nd edn), by the trainer, published by Policy Press. NB: if participants sign up for the monthly e-newsletter produced by Policy Press, they will receive a substantial discount on the book.