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Introduction to Multilevel Modelling

learn-mlms.com focuses on conceptual foundations of multilevel models (MLMs), specifiying them, and interpreting the results. Topics include multilevel data and approaches to dependence, specifying and interpreting fixed and random effects, model estimation, centering, repeated measures and longitudinal models, assumptions testing, and effect sizes in MLMs.

The chapters are:

  1. Introduction
  2. Multiple Regression Review
  3. Approaches to Multilevel Data
  4. Our First Multilevel Models
  5. Adding Fixed Predictors to MLMs
  6. Random Effects and Cross-level Interactions
  7. Model Estimation Options, Problems, and Troubleshooting
  8. Centering Options and Interpretations
  9. Multilevel Modelling with Repeated Measures Data
  10. Multilevel Modelling with Longitudinal Data
  11. Effect Sizes in Multilevel Models
  12. Assumptions

About the Authors

Mairead Shaw is a graduate student in the Quantitative Psychology and Modelling area at McGill University. Her research interests center around effect sizes in multilevel models and measurement considerations for multi-group and replication research.

Dr. Jessica Flake is an Assistant Professor of Quantitative Psychology and Modelling at McGill University. She received an MA in quantitative psychology from James Madison University and a a PhD in Measurement, Evaluation, and Assessment from the University of Connecticut. Her work focuses on technical and applied aspects of psychological measurement including scale development, psychometric modelling, and scale use and replicability.

Funding

These materials were made possible by funding from the APS Fund for Teaching and Public Understanding of Psychological Science. You can read more about the fund here.

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