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E-raamat: Applied Multilevel Analysis: A Practical Guide for Medical Researchers

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(Vrije Universiteit, Amsterdam)
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Applied Multilevel Analysis: A Practical Guide for Medical ResearchersSuurem pilt
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This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians, and they focus on the mathematical background. These books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the application of multilevel analysis in research. It addresses the practical issues that confront those undertaking research and wanting to find the correct answers to research questions. This book is written for non-mathematical researchers and it explains when and how to use multilevel analysis. Many worked examples, with computer output, are given to illustrate and explain this subject. Datasets of the examples are available on the internet, so the reader can reanalyse the data. This approach will help to bridge the conceptual and communication gap that exists between those undertaking research and statisticians.

This is a practical introduction to multilevel analysis, written for non-mathematicians.

Arvustused

' a concise practical guide for non-mathematical researchers beginning to use this technique in their work.' Pradeep Malakar, Institute Food Research

Muu info

This is a practical introduction to multilevel analysis, written for non-mathematicians.
Preface xi
Acknowledgements xii
Introduction
1(5)
Introduction
1(1)
Background of multilevel analysis
2(1)
General approach
3(1)
Prior knowledge
4(1)
Example datasets
4(1)
Software
5(1)
Basic principles of multilevel analysis
6(24)
Introduction
6(4)
Example
10(4)
Intraclass correlation coefficient
14(2)
Random slopes
16(2)
Example
18(4)
Multilevel analysis with more than two levels
22(4)
Example
22(4)
Assumptions in multilevel analysis
26(1)
Comments
27(3)
Which regression coefficients can be assumed to be random?
27(1)
Random regression coefficients versus fixed regression coefficients
28(1)
Maximum likelihood versus restricted maximum likelihood
29(1)
What do we gain by applying multilevel analysis?
30(8)
Introduction
30(1)
Example with a balanced dataset
30(4)
Example with an unbalanced dataset
34(1)
Cluster randomisation
35(2)
Conclusion
37(1)
Multilevel analysis with different outcome variables
38(24)
Introduction
38(1)
Logistic multilevel analysis
38(9)
Intraclass correlation coefficient in logistic multilevel analysis
46(1)
Multinomial logistic multilevel analysis
47(5)
Poisson multilevel analysis
52(5)
Multilevel survival analysis
57(5)
Multilevel modelling
62(24)
Introduction
62(1)
Multivariable multilevel analysis
62(5)
Prediction models and association models
67(18)
Introduction
67(1)
Association models
68(12)
Prediction or prognostic models
80(5)
Comments
85(1)
Multilevel analysis in longitudinal studies
86(22)
Introduction
86(1)
Longitudinal studies
87(4)
Example
91(4)
Growth curves
95(9)
An additional example
101(3)
Other techniques to analyse longitudinal data
104(2)
Comments
106(2)
Extension of multilevel analysis for longitudinal data
106(1)
Clustering of longitudinal data on a higher level
106(1)
Missing data in longitudinal studies
106(2)
Multivariate multilevel analysis
108(17)
Introduction
108(2)
Multivariate multilevel analysis the MLwiN approach
110(7)
Multivariate multilevel analysis: the general approach
117(5)
Comments
122(3)
Sample-size calculations in multilevel studies
125(7)
Introduction
125(1)
Standard sample-size calculations
126(1)
Sample-size calculations for multilevel studies
127(1)
Example
127(1)
Which sample-size calculation should be used?
128(3)
Comments
131(1)
Software for multilevel analysis
132(37)
Introduction
132(1)
Linear multilevel analysis
133(21)
SPSS
133(5)
STATA
138(5)
SAS
143(5)
R
148(5)
Overview
153(1)
Logistic multilevel analysis
154(6)
Introduction
154(1)
STATA
155(1)
SAS
156(2)
R
158(2)
Overview
160(1)
Poisson multilevel analysis
160(5)
Introduction
160(1)
STATA
161(1)
SAS
162(1)
R
163(1)
Overview
164(1)
Multinomial logistic multilevel analysis
165(4)
Introduction
165(1)
STATA
165(2)
Overview
167(2)
References 169(10)
Index 179


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