View Specification DocumentMultilevel and Network Analysis for Social Scientists (M) SPS5077
- Academic Session: 2026-27
- School: School of Social and Political Sciences
- Credits: 20
- Level: Level 5 (SCQF level 11)
- Typically Offered: Semester 2
- Available to Visiting Students: Yes
- Collaborative Online International Learning: No
- Curriculum For Life: No
Short Description
Social populations are connected through people living in the same area, working or studying in the same organisation, or being in the same network. Substantive questions around these phenomena relate to area effects, organisational variations, and peer effects on individual outcomes. Here, multilevel modelling can often be used as a quantitative method. Students will build on the techniques presented in introductory quantitative methods or the Semester 1 courses of the MSc Social Science Research Methods. The necessary theory will be illustrated with real life examples, including key concepts in social network analysis. This course also has a practical element; students will use "R" software to carry out multilevel and network analyses.
Timetable
10 x 2-hour lectures during a 10-week semester.
10 x 1-hour workshop labs during a 10-week semester - lecturer-led.
Requirements of Entry
Require introductory quantitative methods training.
Recommended: working knowledge of R (or similar statistical programming language e.g., Python, Julia)
Excluded Courses
SPS4012
Co-requisites
None
Assessment
Summative 1: 3 Individual problem sets at 500 words each plus statistical output - Worth 50% of course grade
Summative 2: 1 group project at 2,500 words plus statistical output - Worth 50% of course grade
Programme / course convenors and teaching staff will ensure that due consideration is given to students with disabilities, and that reasonable adjustments are implemented wherever possible, in consultation with relevant support services.
A Flexible Assessment approach will be applied, in line with Disability Service recommendations.
This includes:
■ Consideration of alternative assessment formats where appropriate (e.g., adaptations to oral assessments)
■ Implementation of reasonable adjustments on a case-by-case basis.
Course Aims
The course aims to offer students a theoretical and practical presentation of multilevel and network analysis, which will thus enable them to examine social phenomena, both in published work, and in the students' own research. Students will be able to critically assess when the methods described in this course may be useful in helping to answer substantive research questions. Finally, the course has a practical aspect, with the aim to enable students to use R software to carry out their own multilevel and network analysis.
Intended Learning Outcomes of Course
By the end of this course students will be able to:
■ Select and Apply multilevel and network methods appropriate to the research questions and understand their limitations.
■ Conduct analyses of multilevel and network datasets using R software.
■ Effectively communicate statistical findings through both written explanations and appropriate graphical representations.
■ Critically evaluate and synthesise published research on multilevel and network analysis within a relevant social science context.
■ Design and justify the application of multilevel and network analysis within the context of students' own research project.