Purpose This paper aims to discuss multilevel modeling for longitudinal data, clarifying the
circumstances in which they can be used. Design/methodology/approach The authors …

Empirical studies in spatial economics have shown that agglomeration economies may be a
source of the uneven distribution of economic activities and economic growth across cities …

Untitled Page 1 Page 2 SOCIAL NETWORK ANALYSIS for EGO-NETS Page 3 SAGE was
founded in 1965 by Sara Miller McCune to support the dissemination of usable knowledge by …

Importance Quality improvement initiatives demonstrate the contribution of reliable nursing
care to gains in clinical and safety outcomes in neonatal intensive care units (NICUs); when …

This book demonstrates how to use multilevel and longitudinal modeling techniques
available in the IBM SPSS mixed-effects program (MIXED). Annotated screen shots provide …

Throughout the social, medical and other sciences the importance of understanding
complex hierarchical data structures is well understood. Multilevel modelling is now the …

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 …

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

Bayesian methods combine the evidence from the data at hand with previous quantitative
knowledge to analyse practical problems in a wide range of areas. The calculations were …

Nested data structures are ubiquitous in the study of ecology and evolution, and such
structures need to be modelled appropriately. Mixed‐effects models offer a powerful …