The Cathie Marsh Institute are proud to introduce their 2026 short courses. 

All participants will receive state of the art teaching and a lunch voucher as part of the course.

An Introduction to Quantitative Text Analysis in Social Sciences 

Taught by: Maria Pampaka

Location: Ellen Wilkinson Building A3.6

Abstract:  

This course introduces participants to measurement theory and the Rasch model for the construction and validation of measures used in social research (and beyond). It provides an overview of the foundations of measurement from an Item Response Theory (IRT) perspective, with particular emphasis on the assumptions and applications of Rasch models. 

The Rasch model provides a framework for constructing reliable measures (or scales) from sets of items in tests or questionnaires.

 Participants will learn how Rasch models can be used to transform raw responses into meaningful measures and how these measures can be evaluated within a validation framework.

 The principles governing the application of Rasch models will be illustrated through examples from educational measurement and other disciplines, with clear relevance to research in the social and health sciences. Participants will also have the opportunity to work with different models from the Rasch family, including the Dichotomous Model, the Rating Scale Model, and the Partial Credit Model, and to consider applications to their own research.

 The course will be of interest to researchers and practitioners working in areas such as educational assessment, evaluation and satisfaction measurement, tests of skills and knowledge, attitudinal scales, and measures of dispositions and other latent constructs.

 The course will combine lectures and practical sessions organised around the following themes:

• Introduction to Rasch measurement;
• the Dichotomous Rasch Model (with software application);
• the basics of validation using the Rasch measurement framework;
• applications of the Rating Scale Model (for Likert-type items) and the Partial Credit Model (for items with different response structures);
• differential Item Functioning (DIF), optimal functioning of rating scales, and dimensionality.

Course Description

Requirements

Participants should have a basic understanding of introductory statistics. Some familiarity with statistical software and syntax-based commands will be helpful. Example datasets will be provided, but participants are also encouraged to bring their own datasets and measurement problems, possibly with a view to developing a validation report or publication.