图书简介

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 \\ Summary \\ Glossary \\ Challenge Questions With Answers \\ Chapter 7 • The Two-Level Random Coefficients Model \\ Overview \\ SPSS \\ Stata \\ SAS \\ HLM 7 \\ 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 \\ Summary \\ Glossary \\ Challenge Questions With Answers \\ Chapter 9 • Repeated Measures and Heterogeneous Variance Models \\ Overview \\ SPSS \\ SAS \\ Stata \\ 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 \\ Summary \\ Glossary \\ Challenge Questions With Answers \\ Chapter 11 • Cross-Classified Linear Mixed Models \\ Overview \\ Data \\ Model \\ Research Purpose \\ Stata \\ SPSS \\ SAS \\ HLM 7 \\ Summary \\ Glossary \\ Challenge Questions With Answers \\ Chapter 12 • Generalized Linear Mixed Models \\ Overview \\ Estimation Methods \\ Data \\ Model \\ Stata \\ SAS \\ SPSS \\ HLM 7 \\ Summary \\ Glossary \\ Challenge Questions With Answers \\ Appendix 1: Data Used in Examples. Refers to Student Companion Website \\ Appendix 2: Reporting Multilevel Results \\ References \\ Index

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