MRes Criminology (Social Statistics) / Course details

The UK is fortunate in having a rich and growing store of longitudinal studies for researchers to analyse. The course will introduce students to the methodological and statistical skills that will enable them to address questions about the measurement and explanation of change in time.

To provide students with an understanding of different longitudinal designs and the skills needed to conduct appropriate analyses using longitudinal data. Methods covered include the multilevel model for change, and models for investigating event occurrence over time.

• To gain facility in the concepts, designs and terms of longitudinal research;
• To be able to apply a range of different methods of longitudinal data analysis;
• To have a general understanding of how each method represents different kinds of longitudinal processes;
• To be able to choose a design, a plausible model and an appropriate method of analysis for a range of research questions.

The course will comprise 5 days of teaching and learning spread over five weeks. The days of intensive training will be made up of lectures and computer-lab examples and exercises implemented with appropriate statistical software, focusing on the use of R for longitudinal data analysis.

The module will be assets based on an essay of 3000 words that uses longitudinal data analysis methods to answer a substantive question (100%).

Feedback available via Turnitin

• Singer, J., & Willett, J. (2003). Applied longitudinal data analysis: modeling change and event occurrence. Oxford University Press. (available online)
• Long, J. D. (2011). Longitudinal Data Analysis for the Behavioral Sciences Using R. Thousand Oaks, Calif: SAGE Publications, Inc.
• Newsom, J. T. (2015). Longitudinal Structural Equation Modeling: A Comprehensive Introduction. Routledge.

Optional for SRMS

Part time students must take ISM as a pre-requisite and CSDA prior to or in the same semester as LDA