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Discusses variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. This work explains a range of estimation and prediction methods from biostatistics, psychometrics, econometrics and statistics.

Data collected in the social sciences often have a multilevel or clustered structure. From this, we often have research questions that are of a multilevel nature, and multilevel modelling is now widely used across health, economics, demography, education and many other areas to analyze data clustered within units at higher levels. The editors of this essential four-volume set, Multilevel Modelling, are among the leading figures of multilevel m...