National Centre for Research Methods 2022 Training Calendar

1-3 March

Dr Pamela Campanelli

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.

17 March

Professor Vernon Gayle

This is a one day workshop on statistical models for social science data analysis. It will introduce the underlying concepts associated with multivariate analysis using statistical models. The workshop will concentrate on models within the generalized linear modelling framework. It will cover linear regression, and models for binary, categorical, ordered categorical and count data. The focus of the workshop will be on social science applications, and social science data and research questions will be showcased throughout. The emphasis will be on interpreting outputs (e.g. from data analysis software packages) and understanding published results.

18 March

Professor Vernon Gayle

This is a one-day Stata workshop on statistical models for social science data analysis.

The workshop will concentrate on models within the generalized linear modelling framework. It will cover linear regression, and models for binary, categorical, ordered categorical and count data. The focus of the workshop will be on social science applications, and social science data and research questions will be showcased throughout. The emphasis will be on interpreting outputs (e.g. from data analysis software packages) and understanding published results.

24-25 March

Professor Vernon Gayle

The workshop is specifically designed for social scientists, and social science data and examples will be showcased throughout the workshop. The workshop will focus on the research value of longitudinal data and explore sources of longitudinal data. Participants will be introduced to the analysis of repeated cross-sectional data, duration models and models for panel data. The emphasis will be on interpreting outputs (e.g. from data analysis software packages) and understanding results (e.g. in published papers).

1 April

Dr Alexandru Cernat

The course will cover some of the basics and more advanced Latent Growth Models using the lavaan package in R. In addition to the fact that the package is free and open source it also offer great flexibility, being able to estimate most of the models typically used in Longitudinal SEM.
The course covers:

• Introduction to R and lavaan package;
• Short discussion of the SEM framework;
• Latent Growth Models;

The course will be a combination of lecturing and practicals using real world data.

5-6 April

Dr Helen Kara

Ethical research is better quality research. This one day online course (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 comittee 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.

6-14 April

Professor Susan Banducci and others

The NCRM/Exeter Computational Communication Methods Spring School will provide training at introductory and advanced levels, catering for both social scientists and data scientists.

The school will take place at the University of Exeter over two 4-day sessions between 6-14 April 2022 and is co-sponsored by:-

• IDSAI Computational Social Science
• Social Data Science Group, Turing Institute
• Exeter Q-Step

The programme will cover multiple computational approaches, such as machine learning and network analysis, and their application to communication research looking at text, images and social media data.

World-leading experts will deliver workshops, seminars and demonstrations, help desks will offer one-to-one consultations and there will be opportunities for more informal networking.

20-21 April

Kim Ozano and Laura Dean

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.

25 April

Dr Roxanne Connelly

This one-day course is designed for researchers that undertake statistically orientated data analysis for example with data from social surveys, census records, administrative data and other forms of digital data. It will introduce researchers to a range of techniques and tools that allow them to capitalise on improvements in software and programing languages, and computer resources. The course will emphasise the benefits of programing and using software facilities in order to undertake accurate and efficient research that is transparent and reproducible. A special element of the course will introduce techniques that produce publication-ready statistical outputs.

26 April-24 May

Dr Julia Kasmire

Ideally, research is collaborative, well-documented, sharable, and can be reproduced by others (or by the original researchers at a later point in time). Not only does this make a researcher’s job MUCH easier, it makes their work more valuable, citable and extensible. This is increasingly important in light of the ‘crisis of reproducibility’ that risks undermining scientific research in so many fields.

This training series walks you through how to:

• make your research ready for open science,
• apply reproducibility to social science and other “tricky” topics, and
• collaborate, document and share research in diverse contexts.

10 May

Dr Laura Ratcliffe and Dr Leighann Spencer

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.

11 May

Dr Katie Harron and Dr James Doidge

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.

19-20 May

Dr Linda Wijlaars, Dr Ania Zylbersztejn and Dr Pia Hardelid

This 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.

23 May

Jennifer Mason, Vanessa May, Petra Nordqvist, Robert Meckin

Facet Methodology is an approach developed by a team of colleagues at the Morgan Centre for Research into Everyday Lives, University of Manchester.  It is a creative approach to mixing methods and ‘playing with epistemologies’, with the aim of creating insights into our social world. The morning sessions in this face to face workshop will introduce some of the key elements in the approach, and offer examples of how the approach has been used in research. In the afternoon, participants and tutors will work in small groups to consider whether and how a Facet Methodology approach might be useful in participants’ own projects.