Multilevel Analysis: An Introduction to Basic and Advanced Multilevel ModelingSage Publications, 1999 - 266 pagina's The main methods, techniques and issues for carrying out multilevel modeling and analysis are covered in this book. The book is an applied introduction to the topic, providing a clear conceptual understanding of the issues involved in multilevel analysis and will be a useful reference tool. Information on designing multilevel studies, sampling, testing and model specification and interpretation of models is provided. A comprehensive guide to the software available is included. Multilevel Analysis is the ideal guide for researchers and applied statisticians in the social sciences, including education, but will also interest researchers in economics, and biological, medical and health disciplines. |
Inhoudsopgave
Multilevel Theories Multistage Sampling | 6 |
Assumptions of the Hierarchical Linear Model 120 9 Assumptions of the Hierarchical Linear Model | 9 |
Statistical Treatment of Clustered Data | 13 |
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Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling Tom A. B. Snijders,Roel J. Bosker Gedeeltelijke weergave - 1999 |
Veelvoorkomende woorden en zinsdelen
added analysis assumed assumption average calculated called Chapter combined consider contains covariance covariance matrix data set defined denoted dependent variable deviance discussed distribution equal equation error estimated example expected explained explanatory variables expressed Figure fixed effects formula function gender give given group means hierarchical linear model hypothesis implies important independent indicates individual interaction intercept variance interpretation intraclass correlation larger leads less level-one level-one variables level-two macro-units measurements method micro-level multilevel multivariate nesting normal observed obtained outcome parameters population possible presented probability proportional pupils random effects random slope refers regression coefficient relations represented residual residual variance respect sample schools score shows significant sizes specification squared standard standard deviation standard error statistical structure Suppose Table term treated units usually vari variance within-group yields