Multilevel Structural Equation Modeling (Quantitative Applications in the Social Sciences)

 Multilevel Structural Equation Modeling serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the social sciences. As the first book of its kind, this title is an accessible, hands-on introduction for beginners of the topic. The authors predict a growth in this area, fueled by both data availability and also the availability of new and improved software to run these models. The applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra guarantee that this volume will be useful to social science graduate students wanting to utilize such models.

Bruno Castanho Silva is a post-doctoral 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, and statistical methods of causal
inference with observational and experimental data.

Constantin Manuel Bosancianu is a post-doctoral researcher at the Wissenschaftszentrum
Berlin für Sozialforschung (WZB), 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 Littvay is associate professor at Central European University’s
Department of Political Science. 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,
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.