Research Methods in Ageing and Social Change II

Aim

After completing the course, the student should on an advanced level be able to:

• describe, apply, and demonstrate in-depth knowledge of the theoretical and structural bases of longitudinal data and relevant advanced statistical models and its characteristics as well as implications and challenges
• describe and apply knowledge of multi-level and comparative analysis adding macro and meso-data to micro-data from survey and register data
• independently use, plan, and manage longitudinal datasets for further analysis and be able to apply simple and advanced statistical analysis and models to longitudinal data
• apply basic and advanced statistical analysis and statistical models on longitudinal data
• use statistical software in the analysis of longitudinal data
• describe, discuss, and reflect on correct and appropriate methods and results from longitudinal analysis in a scientifically appropriate format
• apply knowledge of ethical aspects on working with longitudinal data

Content

In the course, the focus lies on theoretical concepts and practical applications. The knowledge is offered within longitudinal research methods and questions, together with an in depth understanding of advanced methods of comparative and time-sensitive multilevel research. Furthermore, an in-depth understanding for working with macro, meso and micro-data from survey and register data is offered. Statistical models of focus are within the framework of Structural Equation Models (SEM): Growth Curve Models, Linear Mixed models, and multi-level and comparative analysis.