本帖隐藏的内容
Preface viii
1. Introduction to Multilevel Analysis 1
1.1 Aggregation and disaggregation 2
1.2 Why do we need special multilevel analysis techniques? 4
1.3 Multilevel theories 7
1.4 Models described in this book 8
2. The Basic Two-Level Regression Model 11
2.1 Example 11
2.2 An extended example 16
2.3 Inspecting residuals 23
2.4 Three- and more-level regression models 32
2.5 A note about notation and software 36
3. Estimation and Hypothesis Testing in Multilevel Regression 40
3.1 Which estimation method? 40
3.2 Significance testing and confidence intervals 45
3.3 Contrasts and constraints 51
4. Some Important Methodological and Statistical Issues 54
4.1 Analysis strategy 54
4.2 Centering and standardizing explanatory variables 59
4.3 Interpreting interactions 63
4.4 Group mean centering 68
4.5 How much variance is explained? 69
5. Analyzing Longitudinal Data 79
5.1 Fixed and varying occasions 80
5.2 Example with fixed occasions 81
5.3 Example with varying occasions 93
5.4 Advantages of multilevel analysis for longitudinal data 98
5.5 Complex covariance structures 99
5.6 Statistical issues in longitudinal analysis 104
5.7 Software issues 111
v