An Introduction to Applied Multilevel Analysis

10 credits at Level 7

Module leaders: Dr Mona Kanaan 

Overview

This is an advanced course of interest to those working with multilevel data who wish to further their knowledge of regression analysis. The course introduces applied multilevel regression techniques using real data sets.

Find our more about our Introduction to Applied Multilevel Analysis - HEA00039M module.

Social and medical researchers have long been concerned about the need to properly model complex data structures, especially those where there is a hierarchical structure such as pupils nested within schools or measurements nested within individuals...failure to take account of such structures in standard models can lead to incorrect inferences. What has been less well appreciated is that a failure to properly model complex data structures makes it impossible to capture the complexity that exists in the real world.
Harvey Goldstein

 

 

 

 

 

 

 

 

Entry

A first degree in a health related discipline or social sciences. In addition you should be able to demonstrate that you have knowledge of regression analysis. Applicants are assessed on a case-by-case basis, and we follow the University’s Equal Opportunities policy.

Credits and Cost

Qualification awarded

If you successfully complete this course and the assessment you will be awarded 10 credit points by the University of York, at Level 7 (Masters). You can you also attend the course without completing the assessment.

Cost

Visit our fees and funding page for more information.

To Apply

Postgraduate application form (MS Word , 74kb).

Formal Enquiries 

For informal enquiries about this course email: dohs-pg-enquiries@york.ac.uk.

I really enjoyed the format of the course which includes lectures followed by lab work.

The real data examples given all the way through the course aids understanding the concepts.