very helpful review of both, and then shows how the model and notation can be organized into a single framework for MSEM. Chapter 2 introduces multilevel path models, considering both the random intercept model and the random slopes model. It uses World Values Survey data, Wave 4, from 55 countries to explore the individual-level and country-level factors associated with high self-expression values (importance of civic activism, subjective well-being, tolerance and trust, personal autonomy and choice). Multilevel factor models are the focus of Chapter 3. This chapter uses data from the 2015 wave of the Program for International Student Assessment (PISA) on the use of digital devices in the Dominican Republic to build a two-level CFA, starting with a comparison of the multilevel CFA to the multiple group CFA, then building in random latent variable intercepts and finishing with a multilevel CFA with random loadings. It also includes a useful discussion of measurement invariance. Chapter 4 merges the subject matter of chapters 2 and 3 together into the full multilevel structural equation model (MSEM). The example for this chapter, based on the 2004 Workplace Employment Relations Survey teaching dataset, explores whether employees consider themselves to be under- or over-qualified for their jobs, as affected by their perception of how demanding their jobs are, how responsive their managers, their pay, and—at the company level—number of employees. Chapter 5 concludes the text by addressing some advanced topics such as categorical dependent variables, sampling weights, and missing data, pointing to references where the interested reader can learn more and providing advice on how to approach the technical literature.
Multilevel structural equation models can be quite complex. Indeed, as the authors say, the complexity of the models to be investigated is only limited by the imagination of the investigators (and of course, the data, software, etc.). Given this, readers will especially appreciate this hands-on introduction and the lengths to which the authors have gone to make the material accessible to researchers from a variety of backgrounds.
—Barbara Entwisle
Series Editor
About the Authors
Bruno Castanho Silvais a postdoctoral researcher at the Cologne Center for Comparative Politics (CCCP), University of Cologne. Bruno received his PhD from the Department of Political Science at Central European University and teaches introductory and advanced quantitative methods courses, including multilevel structural equation modeling and machine learning, at the European Consortium for Political Research Methods Schools. His methodological interests are on applications of structural equation models for scale development and causal analysis, as well as statistical methods of causal inference with observational and experimental data.Constantin Manuel Bosancianuis a postdoctoral researcher at the WZB Berlin Social Science Center, in the Institutions and Political Inequality research unit. He received his PhD from the Department of Political Science at Central European University in Budapest, Hungary, and has been an instructor for multiple statistics courses and workshops at the European Consortium for Political Research Methods Schools, at the Universities of Heidelberg, Giessen, and Zagreb, as well as at the Institute of Sociology of the Czech Academy of Sciences. Manuel’s methodological focus is on practical applications of multilevel models, Bayesian analysis, and the analysis of time-series cross-sectional data sets.Levente Littvayis an associate professor at Central European University’s Department of Political Science. He is a recipient of the institution’s Distinguished Teaching Award for graduate courses in research methods and applied statistics with a topical emphasis on political psychology, experiments, and American politics. He received an MA and a PhD in Political Science and an MS in Survey Research and Methodology from the University of Nebraska–Lincoln, has taught numerous methods workshops, and is an academic co-convenor of the European Consortium for Political Research Methods Schools. His research interests include populism, political socialization, and biological explanations of social and political attitudes and behaviors. He often works as a methodologist with medical researchers and policy analysts, co-runs the Hungarian Twin Registry, is an associate editor for social sciences of Twin Research and Human Genetics, and publishes in both social science and medical journals.
Acknowledgments
Throughout the three years in which this monograph was conceived, drafted, and refined, we have benefited from the kind advice and guidance of a great many of our colleagues. Heartfelt thanks go out to M. Murat Ardag, Nemanja Batrićević, Alexander Bor, Amélie Godefroidt, Jochen Mayerl, Martin Mölder, Ulrich Schroeders, and Federico Vegetti for offering feedback at different stages of the project. Without their consistent help, the difficult content we cover would have been even more impenetrable. We also extend our thanks to participants in the workshops and courses on multilevel structural equation models that we have led during this time. These include the October 2017 MSEM workshop at the University of Bamberg organized by Thomas Saalfeld, especially to Sebastian Jungkunz; the October 2018 MSEM workshop at the Meth-Lab of the Katholieke Universiteit Leuven organized by Amélie Godefroidt and Lala Muradova; two courses in multilevel structural equation modeling (MSEM) taught at the 2016 and 2017 editions of the European Consortium for Political Research (ECPR) Summer School in Methods and Techniques at Central European University in Budapest, Hungary; and, finally, a course in advanced structural equation modeling (SEM) taught at the 2017 edition of the same Summer School. Their questions have repeatedly challenged our thinking, in addition to highlighting areas where our explanations could be clearer.
Last but not least, we owe a debt of gratitude to Yves Rosseel for creating the lavaan scripts for some of the models in this book and Linda Muthén of the Mplus team for her speedy response to our questions. Whatever errors have persisted in the book are entirely our own and represent but a small sample of what could have been had the previously mentioned colleagues not generously shared their time, thoughts, and expertise with us.
Our work on this manuscript has been supported in many other ways as well, chief among them being the support staff at the various methods schools and workshops where we have tested our ideas. We wish to thank Miriam Schneider and Dagmar Riess at the University of Bamberg, Anna Foley and Becky Plant from ECPR’s Central Services, and the local organizing team in Budapest, especially Carsten Q. Schneider and Robert Sata. We are also grateful for the opportunity to teach these courses to Derek Beach and Benoît Rihoux, who join Levente Littvay as the academic conveners of the ECPR Methods Schools.
Separately, we wish to extend our gratitude to additional valued colleagues. Manuel Bosancianu wishes to thank Zoltán Fazekas for answering many multilevel modeling (MLM) questions over the years, as well as Macartan Humphreys for his feedback and support. Levente Littvay wishes to thank Elmar Schlüter, Bengt Muthén, and Geoffrey Hubona for the MSEM-specific inspiration and, more generally, all the people who handed him QASS series books throughout his studies: Kevin Smith (v22, v79), Brian Humes (v122), Julia McQuillian (v143), Craig Enders (v136), Jim Bovaird (v95, v116, v144, and probably more), and to the loving memory of Allan McCutcheon (v64, but also v126, v119), who started his post-PhD career even before his PhD started by putting him in touch with Tamás Rudas (who wrote v119 and v142). These people, along with Les Hayduk and Mike Neale, shaped his methodological thinking the most and gave him the tools to pass knowledge on to the next generation of outstanding scholars, such as his coauthors and many of the people thanked above for their help and support. This book is dedicated to them as it is very much also their contribution (although he is fairly sure Les and Tamás would not approve much of what is written here, but maybe the final paragraph).
Collectively, we would like to express our gratitude to Barbara Entwisle, Katie Metzler, Megan O’Heffernan, and Helen Salmon from SAGE for their logistic support, advice,
