This module is not currently running in 2021 to 2022.
This module builds on already established statistical knowledge from previous courses, and aims at further developing key statistical skills. Students will be enabled to apply these skills to become more proficient researchers. In particular, the knowledge gained through this course should help students with coursework in their substantive modules and with their dissertation. Learning will be oriented towards:
i. Assessing the strengths and limitations of various techniques to model hierarchical data including
o Interaction terms when the number of higher level units is small
o Clustered standard errors and fixed effects models
o Multilevel models
ii. Learning how to appropriately use statistical methods of analysis, in particular multilevel models, using statistical software to answer research questions
iii. Learning how to interpret the outcome of multilevel models, contextualise the results within broader theories, visualize the main findings, and communicate the findings to academic and lay audiences.
On successfully completing the module students will be able to:
1. Demonstrate a systematic understanding of the core problems and concepts of analysing hierarchical data;
2. Understand (and critically evaluate) the difference between various approaches to deal with hierarchical data, such as interaction terms (when there are only few higher level units), fixed effects, and random effects (aka multilevel models);
3. Demonstrate an ability to apply the methods and techniques they have learned, but also their limitations, and use them to carry out their own research projects;
4. Demonstrate an ability to read, understand and report/represent (e.g. tables, graphs) the results of multilevel models;
5. Critically evaluate the assumptions and underlying concepts of multilevel models (e.g. non-independence of observations);
University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. However, courses, services and other matters may be subject to change. Please read our full disclaimer.
