In this review, we explore recent developments in the area of linear and nonlinear
generalized mixed-effects regression models and various alternatives, including …

The search for appropriate statistical methods for hierarchical, multilevel data has been a
prominent theme in educational statistics over the past 15 years. As a result of this search …

Using a conceptual, non-mathematical approach, the updated Third Edition provides full
coverage of the wide range of multivariate topics that graduate students across the social …

Linear structural equation modeling has become an indispensable methodology for
specifying, estimating, and testing hypothesized interrelationships among a set of …

Applauded for its clarity, this accessible introduction helps readers apply multilevel
techniques to their research. The book also includes advanced extensions, making it useful …

Hierarchical linear models: Applications and data analysis methods. Hierarchical linear
models: Applications and data analysis methods. Citation Bryk, AS, & Raudenbush, SW (1992) …

Multilevel analysis is a methodology for the analysis of data with complex patterns of
variability, with a focus on nested sources of such variability–pupils in classes, employees in …

Organizational researchers are increasingly interested in model ing the multilevel nature of
organizational data. Although most organi zational researchers have chosen to investigate …

Multilevel modelling is a data analysis method that is frequently used to investigate
hierarchal data structures in educational, behavioural, health, and social sciences …

This paper develops a preliminary study to explore the determinants of capital structure of
Chinese-listed companies using firm-level panel data. The findings reflect the transitional …