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Course Syllabus

Master 2022/2023

Multilevel Modeling

Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Type: Elective course (Modern Social Analysis)
Area of studies: Sociology
Delivered by: Department of Sociology
Where: Saint-Petersburg School of Social Sciences
When: 2 year, 2 module
Mode of studies: offline
Open to: students of all HSE University campuses
Instructors: Eduard Ponarin, Olesya Vólchenko
Master’s programme: Modern Social Analysis
Language: English
ECTS credits: 3
Contact hours: 28

Course Syllabus

Full SyllabusAsk Question

Abstract

Analysts have to deal with hierarchical data structures increasingly more often. In particular, one encounters them in the context of cross - country comparisons. Classic regression methods applied to such data result in biased estimates. There are several ways to deal with this problem. One popular method is the multilevel regression. This course covers the basic tenets of this method with applications to international survey research data. The course assumes the student's knowledge of linear and binary logistic regression modelling.
Learning Objectives

Learning Objectives

  • The aim of the course is to show how to work with hierarchical data structures using R.
Expected Learning Outcomes

Expected Learning Outcomes

  • Being able to access the results of multilevel modeling and interpret them statistically and sociologically
  • To apply multilevel modeling techniques in practical research
  • To model individual cases within groups choosing the best model
Course Contents

Course Contents

  • Principles of multilevel modelling
  • Hierarchical OLS – model
  • Hierarchical binary logistic model
  • Non-hierarchical multilevel model
Assessment Elements

Assessment Elements

  • non-blocking Mid-term presentation of the individual project proposal
  • non-blocking Midterm exam
  • non-blocking Final essay
Interim Assessment

Interim Assessment

  • 2022/2023 2nd module
    0.25 * Mid-term presentation of the individual project proposal + 0.5 * Final essay + 0.25 * Midterm exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Multilevel analysis: An introduction to basic and advanced multilevel modeling. (1999). SAGE Publications.

Recommended Additional Bibliography

  • Gelman, A., & Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.

Authors

  • VOLCHENKO OLESYA VIKTOROVNA
  • PONARIN EDUARD DMITRIEVICH
  • TSVETKOVA EKATERINA ANDREEVNA