Presenter: Dr Pierre Walthéry
This short course aims to introduce participants to time diary analysis, a multidisciplinary field which has made a sustained contribution to social science over the last 50 years. It is targeted at academics, doctoral students, post-doctoral as well as public or private sector researchers interested in studying the way people spend their time throughout the day. It requires basic to intermediate prior knowledge of statistics and basic experience with statistical programming.
Presenter: Professor Paul Lambert
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.
Presenter: Dr Kevin Ralston
This one-day course showcases suitable techniques for mediation analyses.
In statistics, a mediation model seeks to identify and explain the mechanism or process that underlies an observed relationship between an independent variable and a dependent variable via the inclusion of a third variable, known as a mediator variable.
The course illustrates approaches for undertaking mediation analysis in Stata and considers related issues of moderation/interaction and confounding. The coverage includes approaches to examine more complex mediation models. This takes in models where both mediation and moderation occur and categorical outcome models. In addition to Stata, participants will be directed to a range of resources for conducting mediation analysis in other software such as R and SPSS.
It is most suited to empirical social science researchers with some knowledge of statistical data analysis methods. The course is a good follow on for those who have experience of regression and a suitable stepping stone for those interested in structural equation modelling.
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.
We will begin by outlining the fundamental problem of casual thinking with the aid of the potential outcomes approach. Following this, we will explore how randomising people (or schools, or clinics, or whatever) to different interventions and comparison groups makes it easier to draw inferences about the causal impact of those interventions.
Sessions will then cover when randomisation is likely feasible and ethical; how to randomise and ways to limit the possible random assignments; key decisions on the level of randomisation (e.g., individual or a larger “cluster”); how to choose a sample size; how to represent an RCT design in a regression model; and finally, how to address common pragmatic issues such as participant “compliance”, attrition, and other threats to study validity.
Presenter: Dr Rob Berry
This course is running over two mornings (09:30 – 12:30). Participants will learn how to automatically generate a batch of multiple maps from a single map layout template in QGIS, using the QGIS Atlas tool. Anyone who uses QGIS to produce maps is likely to have the need to create a series of maps of the same theme for multiple regions / points of interest. The ‘manual’ way of approaching this is to set-up a different map design template (QGIS Print Layout) for each geographical feature (e.g. region or point) in the database, but this can be a time-consuming and error-prone process, and multiple maps cannot be easily updated if changes to the design are required. The Atlas-based method requires only one map layout per theme, which has major advantages for improving the speed and quality of map production in certain circumstances – is it not always the optimal solution, and the limitations of this approach will be highlighted during the session.
Introducing Institutional Ethnography: An Interdisciplinary Feminist Approach to Social Research, 11-12 October 2021
Presenters: Dr Orla Murray, Dr Liz Ablett and Dr Adriana Suarez-Delucchi
This 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 a comprehensive feminist ontology of how the social world works which advocates using a form of standpoint to explore from specific perspectives. IE research ‘takes sides’, often researching as, with, and/or for, marginalised groups who are often made invisible by, or excluded from, organisations and institutions. The focus on texts – conceptualised as replicable materials objects that carry messages – allows IE researchers to ethnographically explore the organising power of language and institutions, made material in institutional texts which act as bridges between different people and places.
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 or 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.
Presenter: Dr. Tarek Al Baghal
This course provides an overview of sampling techniques frequently used in survey designs. This relies on applied statistical methods focusing on the design of probability samples to be used for data collection. Sample designs are driven by analytic goals of an investigator, but this is not an analysis course. In particular, this course focuses on the principles of designing and selecting samples of individuals. An introduction to several sampling design will be given, including simple random sampling, stratification, cluster sampling, systematic sampling, multistage sampling, and probability proportional to size sampling. These principles are also discussed in terms of the effects on inference to the population of interest, the key goal of survey research. Participants will be also encouraged discuss their own research questions and studies to identify practical sampling solutions, to make the classes more interactive and very practical.
Multilevel Modelling: A robust analytical method for randomised controlled educational trials, 25-28 October 2021
This four day course (running from 10am – 4pm each day) will focus on the conceptual understanding of multilevel modelling and its relevance for robust analysis of evidence from randomised controlled trials, with case studies from educational trials. It will focus on ‘meaning’ and application of multilevel models instead of computations. The course will run for four days with the first day focusing on the transition from linear regression models to multilevel models. Practical examples with simple exercises will be used to motivate the need for a more robust approach than t-tests or linear regressions in educational trials. The different sources of variability will be discussed as well as their implications on effect size. The course will primarily be taught in R, but we would also be able to support individual exercises in SAS and STATA. This is an intermediate course that requires good understanding of linear regression model as a prerequisite.
Presenter: Dr Will Slocombe
This 15-person workshop introduces the basics of narrative theory and narratological principles, and their relevance to communicating research. Using this understanding of narratology, the workshop will demonstrate how an awareness of ‘telling stories’ can be employed as a framework for communicating research. The focus is primarily on thesis writing, but applies to other outputs too, such as articles and monographs. Participants are encouraged to workshop their ideas and pay particular attention to the principle of effective communication to non-specialist audiences. To that end, it is appropriate to any disciplinary background, and participants are assumed to have no pre-existing knowledge of narratology, but the course is most beneficial to those beginning their research or those in their writing-up period.
Presenter: Dr Helen Kara
This online course will outline creative research methods and show you how to use them appropriately at every stage of 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 more conventional research methods and are often particularly useful when addressing more complex research questions. You will have the opportunity to try applying some of these methods in practice, and attention will be paid to ethical issues throughout. The course will include plenty of practical advice and tips on using creative methods in research.
Presenter: Dr Stuart Reeves
Human-computer interaction (HCI) is an ever-more pervasive phenomenon. In fact, avoiding any kind of interaction with digital technologies has become a purposeful and quite challenging act in many modern societies. In this way HCI has the potential for widespread relevance considerably beyond its initial disciplinary origins stemming largely from university computer science and psychology departments.
Simultaneously, approaches from the human sciences (and arts and humanities) have pushed well into HCI’s mainstream. One approach that has had significant formative impact in HCI is, broadly, sociological interactionism; that is, understanding interaction with / around digital technologies, infrastructures and services as constitutively interactional in nature.
This course will explore one formative strand of interactionism: video-based studies of social interaction with / around digital technologies (e.g., in everyday life), informed by traditions of ethnomethodology and conversation analysis.
The course will contextualise video analysis both in terms of human-computer interaction as everyday, routine phenomena, and with respect to HCI as a field (and its connections with both technical and sociotechnical fields of research). By looking at video analysis through the lens of ethnomethodology and conversation analysis, coupled with a perspective on the disciplinary challenges such work potentially faces, this course will provide a broad introduction to doing studies in this form: how they can be conceived of and what outcomes they might produce.
This online course 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.
Presenter: Dr Nick Bearman
In this one day online course (taught over 2 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.
Click on the drop down links to the left to find out more information regarding the NCRM course programme. Links to the booking forms can also be found in the drop downs or by following this link.
Please note, unless otherwise stated there is a course fee for attendance. For most courses this is set at £30 per day for students and £60 per day for academics.