FAIR Workshop on Analyzing Intervention Effects in Small and Single-Case Data
This workshop offers a comprehensive introduction to analyzing single-case data, a powerful approach for evaluating interventions at the individual level. The workshop is divided into three parts. The first part introduces fundamental concepts of single-case research and the scan package for data handling and visualization, including creating, structuring, and plotting data. It also covers analytical techniques like overlapping indices and piecewise linear regression, with practical exercises to prepare participants for advanced methods. The second part focuses on more complex scenarios, introducing multilevel and multivariate piecewise regression models for analyzing multiple experiments and outcome variables. It concludes with a discussion on using randomization tests for non-parametric data as well as statistical power analysis in experimental design planning. In the third part, participants will apply the presented methods to their own data sets and discuss the results.
When and where
Date and Time: April 1st and 2nd, 2025
Location: TU Dortmund University, CDI building, Room 022/023, Vogelpothsweg 78, 44227 Dortmund
Requirements
Participants should have a working knowledge of statistics at the level of BSc psychology (e.g., linear regression, t-tests). Further, they should bring their own notebook with R and R-packages scan and scplot installed. Participants should also bring an own single-case data set, for which analysis strategies will be discussed in the final part of the workshop.
Registration
In order to register for this workshop, please fill out the following form:
Part 1: Introduction to analyzing data from single-case designs
Prof. Timo Lüke, University of Kassel
April 1st, 8:00-12:15
Single-case experimental designs provide a rigorous framework for studying interventions at the individual level. In this workshop, we will introduce the fundamental concepts of single-case research and familiarize participants with the scan package for data handling and visualization. We will cover key topics such as creating, structuring, and displaying single-case data, as well as generating single-case data plots. Moving into data analysis, we will explore how to describe single-case data and introduce analytical techniques, including overlapping indices and piecewise linear regression. Participants will gain practical experience in structuring and analyzing single-case data, preparing them for more advanced statistical approaches covered in the second part of the workshop.
Timo Lüke
Timo Lüke is professor of inclusion-oriented diagnostics at the University of Kassel, Germany. His research interests include assessment and diagnostics in the context of inclusive classrooms and learners with disabilities or at risk. He is a special education teacher with a focus on learning and intellectual disabilities, and enthusiastic user of single-case research methods.
Part 2: Advanced topics in analyzing data from single-case designs
Prof. Patrick Onghena, KU Leuven
April 1st, 13:15-17:30
Single-case researchers seldom need to analyze data from only one single-case experiment and from only one outcome variable. Therefore, in this part of the workshop, we will introduce multilevel piecewise regression models and multivariate piecewise regression models. Furthermore, in case the parametric assumptions of these statistical models are considered implausible and missing data impede the statistical inference, randomization tests might come to the rescue. This part of the workshop ends with a discussion and exercises on the added value of statistical power analysis in the planning phase of a single-case experimental design.
Patrick Onghena
Patrick Onghena is professor of educational and behavioral statistics and methodology at KU Leuven, University of Leuven, Belgium. His research interests include single-case experimental designs, distribution-free statistical inference, meta-analysis, systematic reviews, mixed methods research, and research on statistics education and probabilistic reasoning.
Part 3: Analyzing and discussing participants‘ own data
April 2nd, 8:00-12:15
In this part of the workshop, participants will use their own single-case or small data sets. The goal is to present both data and underlying research hypothesis, and to apply the methods and ideas presented in the workshop to their own data. We will first work in small groups, before presenting and discussing results in the audience.
For further questions, please contact tobias.kuhntu-dortmundde