Application of Multilevel Analysis for Quantitative Social Science

Description:

Prerequisite: Students should have a working understanding of a regression model, and some experience having used either SPSS or STATA software packages.

Day one (12:00pm - 5pm)

Day one will consist of theoretical parts and one practical session. Participants will be given an introduction to multilevel modelling (MLM) and will learn the theoretical basis of random intercept models. They will then apply what they have learnt in a practical session, which will teach students how to conduct and interpret random intercept and random slope models in SPSS and STATA.

Day two (9:30am - 5pm)

On the second day participants will learn about random slope models, and how to add contextual variables and interpret interactions. Participants will also learn about practical applications of MLM. They will also be introduced to different ways in which MLM results can be presented in their papers. In the practical afternoon session participants will be given the opportunity to work on their own data and or use the data provided to them to answer their own research question. The students are given the opportunity to present this work to the class, and get expert feedback from the course leaders. This provides an informal, comfortable environment in which participants can share their thoughts, feelings and concerns of their own MLM data analyses with the staff experts and other peers. This will provide participants with a unique, innovative opportunity to understand how MLM methods apply to different disciplines, which is important for the advancement of social sciences.

The course will be innovative in its approach to teaching MLM by providing both theoretical and practical parts, which give participants the opportunity to apply what they have learnt. Students will have the opportunity to informally present their own work, which will provide a vital opportunity to receive feedback from experts and peers. It will also give students a deeper understanding of interdisciplinary uses of MLM. 

Learning outcomes:

• You will understand the ideas behind Multi-level analysis
• You will learn the pros and cons of the method
• You will learn when or when not to apply the model
• You will learn how to run your own multi-level models
• You will learn how to interpret the analysis outcomes
• You will learn how to interpret multilevel analysis outcomes of others

Cost:

Free to Kent postgraduates and free to PGRs in Kent doctoral training partnership institutions,*

£30 for all other PGRs

*Kent is in a DTP with: UEA, Essex, Reading, RHUL, Surrey, Sussex, Goldsmiths, Open University, Birkbeck, The Courtauld Institute, SOAS, Roehampton, City University London

Website and registration:

https://www.kent.ac.uk/graduateschool/skills/advancedtraining.html

Region:

South East

Keywords:

Mixed Methods Data Handling and Data Analysis

Related publications and presentations:

Mixed Methods Data Handling and Data Analysis

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