发帖
雷达卡
我费了好大劲搞来了一个 现在低价分享给大家！一样的书 这个虽然没那么大 但是我看了一下也是非常清晰啊！足够用了！
Preface ………………………………………………………………………………………………. v
1 Introduction ..............................................................................................................................1
1.1 Conceptual framework of multilevel modeling ................................................................. 1
1.2 Hierarchically structured data........................................................................................... 3
1.3 Variables in multilevel data .............................................................................................. 4
1.4 Analytical problems with multilevel data .......................................................................... 6
1.5 Advantages and limitations of multilevel modeling .......................................................... 8
1.6 Computer software for multilevel modeling .................................................................... 10
2 Basics of linear multilevel models .........................................................................................13
2.1 Intraclass correlation coefficient (ICC).......................................................................... 13
2.2 Formulation of two-level multilevel models .................................................................. 15
2.3 Model assumptions ......................................................................................................... 17
2.4 Fixed and random regression coefficients...................................................................... 18
2.5 Cross-level interactions................................................................................................... 20
2.6 Measurement centering................................................................................................... 21
2.7 Model estimation.............................................................................................................23
2.8 Model fit, hypothesis testing, and model comparisons.................................................. 27
2.8.1 Model fit .............................................................................................................. 27
2.8.2 Hypothesis testing ............................................................................................... 28
2.8.3 Model comparisons ............................................................................................. 30
2.9 Explained level-1 and level-2 variances......................................................................... 30
2.10 Steps for building multilevel models............................................................................ 33
2.11 Higher-level multilevel models .................................................................................... 37
3 Application of two-level linear multilevel models................................................................39
3.1 Data ................................................................................................................................. 39
3.2 Empty model ...................................................................................................................42
3.3 Predicting between-group variation ............................................................................... 48
3.4 Predicting within-group variation................................................................................... 53
3.5 Testing level-1 random................................................................................................... 57
3.6 Across-level interactions ................................................................................................ 62
3.7 Other issues in model development................................................................................ 66
4 Application of multilevel modeling to longitudinal data...................................................73
4.1 Features of longitudinal data............................................................................................ 73
4.2 Limitations of traditional approaches for modeling longitudinal data ............................. 74
4.3 Advantages of multilevel modeling for longitudinal data................................................ 75
4.4 Formulation of growth models......................................................................................... 75
4.5 Data and variable description........................................................................................... 77
4.6 Linear growth models ...................................................................................................... 79
4.6.1 The shape of average outcome change over time ................................................. 80
4.6.2 Random intercept growth models......................................................................... 80
4.6.3 Random intercept-slope growth models ............................................................... 84
4.6.4 Intercept and slope as outcomes ........................................................................... 86
4.6.5 Controlling for individual background variables in models ................................. 88
4.6.6 Coding time score................................................................................................. 89
4.6.7 Residual variance/covariance structures............................................................... 91
4.6.8 Time-varying covariates....................................................................................... 95
4.7 Curvilinear growth models .............................................................................................. 98
4.7.1 Polynomial growth model .................................................................................... 98
4.7.2 Dealing with collinearity in higher order polynomial growth model ................. 100
4.7.3 Piecewise (linear spline) growth model.............................................................. 106
5 Multilevel models for discrete outcome measures ........................................................... 113
5.1 Introduction to generalized linear mixed models......................................................... 113
5.1.1 Generalized linear models................................................................................. 113
5.1.2 Generalized linear mixed models...................................................................... 115
5.2 SAS Procedures for multilevel modeling with discrete outcomes .............................. 116
5.3 Multilevel models for binary outcomes........................................................................ 117
5.3.1 Logistic regression models................................................................................ 117
5.3.2 Probit models..................................................................................................... 118
5.3.3 Unobserved latent variables and observed binary outcome measures ............. 119
5.3.4 Multilevel logistic regression models .............................................................. 119
5.3.5 Application of multilevel logistic regression models....................................... 120
5.3.6 Application of multilevel logit models to longitudinal data ............................ 136
5.4 Multilevel models for ordinal outcomes....................................................................... 139
5.4.1 Cumulative logit models ................................................................................... 139
5.4.2 Multilevel cumulative logit models .................................................................. 141
。。。
Index............................................................................................................................................. 259
京公网安备 11010802022788号
