This workshop will introduce participants to the basics of assembling longitudinal cross-sample and within-sample panel datasets as well as how to conduct trend analyses using STATA. It is designed for social scientists who wish to conduct longitudinal data analyses either as a core component of their projects or as a complementary component to their ongoing research. The session will explore the key differences between types of longitudinal data and the key theoretical concepts that are core to conducting analyses of these types of data, including fixed and random effects, time variables, and the utility of multilevel modelling in trend analyses.

The session will cover the most important considerations involved in creating a cross-time single sample panel as well as explore the core practical skills required to merge, clean, and assemble repeated cross-sample data. During this workshop, participants will generate a new dataset, drawing on existing sources. They will also be introduced to the basics of running trend analyses on these data.

All exercises and sample analyses will be done using STATA, providing participants with important introductory skills and the sample coding that they will need to start applying these techniques in their own projects. Visit the workshop details page for information on how to download and install a temporary STATA license: https://www.kindinstitute.net/workshop-outlines/modzelewski-january-2025

In this workshop, Dr. Gill will walk participants through the foundations of machine learning and its relevant applications in the social sciences. He will outline how machine learning can be employed to handle big data and introduce you to some of the basic tools one would need to get started, including some of the many data sources from which social scientists might wish to pull data. He will explore the key ethical matters that must be considered, the regulatory frameworks currently in place that limit acquisition and use of data, and some of the ways in which data science through machine learning can help contribute to positive societal changes.

In this workshop, Prof. Crotty will walk participants through various approaches to coding qualitative data. She will outline the difference between deductive and inductive coding approaches, as well as guide participants step-by-step through the data collection process leading up to the coding and analysis phase. This workshop will focus mainly on data collected through semi-structured interviews but will offer some discussion of other types of data collection methods as well.

Participants will have the opportunity to conduct a sample semi-structured interview, generate a dataset based on this interview, as well as begin analyzing the data. They will have a chance to discuss their experiences of conducting the interview and coding the data, working through the limitations and benefits of different coding approaches and how they apply in different contexts.

Focus groups, traditionally used in market research, have become increasingly popular across the social sciences in the last two decades. Today, they are widely used for qualitative data collection both in academic and applied research (such as evaluation research). With the COVID pandemic, they have been adapted (with some success) for online use. In political science and international relations too, focus groups are particularly useful for research that examines everyday narratives and micro-level experiences and beliefs of "ordinary" citizens and for policy research (Stanley 2016, Cyr 2019). They can also be useful for exploratory research aiming to generate hypotheses or categories (including as part of mixed methods designs, for example a subsequent survey research).

This workshop is a short introduction to the method: its logic, key steps, uses and difficulties. By the end of the workshop, participants should have a good idea of what focus groups are and what they can be used for.

This workshop will introduce participants to the basics of social science discourse analysis (and similar approaches such as narrative analysis), i.e. to a family of (interpretive) approaches that emphasise the constructed nature of the social and the importance of struggles for interpretive hegemony for the definition of social and political “realities”.

It starts with a brief introduction to the theoretical and epistemological bases of (poststructuralist) discourses analysis, then moves on to practical exercises whose aim is to illustrate how discourse analytical research is concretely done. These exercises will also raise issues such as validity criteria, the nature and limits of interpretation, and how to write up this type of research convincingly. Finally, participants will have an opportunity to briefly consider various “schools” of discourse analysis and discuss the usefulness of discourse analytical work for various disciplines.