This book introduces the foundations of multilevel models, using Monopoly® rent data, from the classic board game, and the statistical program Stata®. Widespread experience with the game means many readers have a head start on understanding these models. The small-data set, 132 rent values for 22 properties clustered by the four sides of the playing board, combines with extensive graphical displays of data and results so all readers can see core multilevel ideas in action at a granular level. Two chapters on standard statistical models, one-way analysis of variance and multiple regression, help readers see how multilevel models rely on but also extend these monolevel ideas. Chapters present three basic multilevel models for cross-sectional analyses analysis of variance, analysis of covariance, and random coefficients regression and one basic developmental model for longitudinal analyses. Troubleshooting guidance, combined with close examination of data patterns, and careful inspection of model parameters, all help readers better grasp what model results mean, when model results should or should not be trusted, and how model results link back to core theoretical questions. Consequently, readers will develop a sense of best practices for building and diagnosing their own multilevel models. Those who complete the volume can readily apply what they have learned to more complex datasets and models and adapt available online Stata do files to those projects. Any social scientist working with data clustered in time, in space, or in both, and seeking to learn more about how to use, interpret, or teach these models, will find the book useful.
This book introduces the foundations of multilevel models, using Monopoly® rent data from the classic board game, and the statistical program Stata®. Widespread experience with the game means many readers have a head start on understanding these models.
1. First Steps.
2. From Title Deeds to Dataset.
3. Describing the
Dataset Statistically.
4. Monolevel Models Part I: OLS (Ordinary Least
Squares) Regression.
5. Monolevel Models Part II: One-way Analysis of
Variance (ANOVA). 6 .First Multilevel Model: No Predictors.
7. Second
Multilevel Model: Adding Guesthouses and Hotels.
8. Third Multilevel Model:
Do Neighborhoods Alter Hotel Rent Impacts?
9. Longitudinal Data: Did Some
Properties Develop Faster than Others?
10. Centering and Multileveling
Predictors.
11. Next Steps
Ralph B. Taylor is Professor Emeritus of Criminal Justice at Temple University, USA, and a fellow of the American Society of Criminology. He holds a PhD in social psychology from Johns Hopkins University and has authored or co-authored over 90 refereed journal articles in criminal justice, criminology, social psychology, sociology, public health, urban affairs, and law and human behavior. His externally funded research has been supported by the National Science Foundation, the National Institute of Mental Health, the National Institute of Justice, and other sources. He has previously served on the editorial boards of Criminology and Public Policy, Environment & Behavior, Journal of Criminal Justice, Journal of Quantitative Criminology, Justice Quarterly, and Social Psychology Quarterly. He is the author of Research Methods in Criminal Justice (McGraw-Hill, 1994), Breaking Away from Broken Windows (Westview, 2001), Community Criminology (New York University Press, 2015), and Human Territorial Functioning (Cambridge University Press, 1988); the editor of Urban Neighborhoods (Praeger, 1986); and a co-editor of Crime and Justice 2000 Volume 1: Continuities and Change (National Institute of Justice, 2000). He began teaching multilevel models to graduate students in the late 1990s. Lists of publications and descriptions of research interest areas appear at www.rbtaylor.net .
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