Multilevel modeling : applications in STATA, IBM, SPSS, SAS, R, & HLM /: applications in STATA, IBM, SPSS, SAS, R, & HLM. (2019)

• Record Type: Book
• Further Information: Note: George David Garson.
• Authors: Garson, G. David
• Contents: Preface; Acknowledgments; About the Author; Chapter 1 • Introduction to Multilevel Modeling; Overview; What Multilevel Modeling Does; The Importance of Multilevel Theory; Types of Multilevel Data; Common Types of Multilevel Model; Mediation and Moderation Models in Multilevel Analysis; Alternative Statistical Packages; Multilevel Modeling Versus GEE; Summary; Glossary; Challenge Questions With Answers; Chapter 2 • Assumptions of Multilevel Modeling; About This Chapter; Overview; Model Specification; Construct Operationalization and Validation; Random Sampling; Sample Size; Balanced and Unbalanced Designs; Data Level; Linearity and Nonlinearity; Independence; Recursivity; Missing Data; Outliers; Centered and Standardized Data; Longitudinal Time Values; Multicollinearity; Homogeneity of Error Variance; Normally Distributed Residuals; Normal Distribution of Variables; Normal Distribution of Random Effects; Convergence; Covariance Structure Assumptions; Summary; Glossary; Challenge Questions With Answers; Chapter 3 • The Null Model; Overview; Testing the Need for Multilevel Modeling; Likelihood Ratio Tests; Partition of Variance Components; Examples; Summary; Glossary; Challenge Questions With Answers; Chapter 4 • Estimating Multilevel Models; Fixed and Random Effects; Why Not Just Use OLS Regression?; Why Not Just Use GLM (ANOVA)?; Types of Estimation; Robust and Cluster-Robust Standard Errors; Summary; Glossary; Challenge Questions With Answers; Chapter 5 • Goodness of Fit and Effect Size in Multilevel Models; Overview; Goodness of Fit Measures and Tests; Effect Size Measures; Effect Size and Endogeneity; Summary; Glossary; Challenge Questions With Answers; Chapter 6 • The Two-Level Random Intercept Model; Overview; SPSS; Stata; SAS; HLM 7; R; Summary; Glossary; Challenge Questions With Answers; Chapter 7 • The Two-Level Random Coefficients Model; Overview; SPSS; Stata; SAS; HLM 7; R; Significance (p) Values for Variance Components; Summary; Glossary; Challenge Questions With Answers; Chapter 8 • The Three-Level Unconditional Random Intercept Model with Longitudinal Data; Overview; SPSS; Stata; SAS; HLM 7; R; Summary; Glossary; Challenge Questions With Answers; Chapter 9 • Repeated Measures and Heterogeneous Variance Models; Overview; SPSS; SAS; Stata; R; HLM 7; Summary; Glossary; Challenge Questions With Answers; Chapter 10 • Residual and Influence Analysis for a Three-Level RC Model; About This Chapter; Overview; Why Residual Analysis?; Data; Model; Model Diagnostics; SAS; Stata; SPSS; HLM 7; R; Summary; Glossary; Challenge Questions With Answers; Chapter 11 • Cross-Classified Linear Mixed Models; Overview; Data; Model; Research Purpose; Stata; SPSS; SAS; HLM 7; R; Summary; Glossary; Challenge Questions With Answers; Chapter 12 • Generalized Linear Mixed Models; Overview; Estimation Methods; Data; Model; Stata; SAS; SPSS; HLM 7; R; Summary; Glossary; Challenge Questions With Answers; Appendix 1: Data Used in Examples. Refers to Student Companion Website; Appendix 2: Reporting Multilevel Results; References; Index;
• Edition: 1st
• Publisher Details: Los Angeles : SAGE
• Publication Date: 2019
• Extent: 1 online resource
• Subjects: 519.54028553; Social sciences -- Statistical methods -- Computer programs; Social sciences -- Mathematical models; Social sciences -- Data processing; R (Computer program language)
• Languages: English
• ISBNs: 9781544319278
• Related ISBNs: 9781544319292
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
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