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Part Ⅰ Analysis of Survival and Longitudinal Data 3

Chapter 1 Non-and Semi-Parametric Modeling in Survival Analysis Jianqing Fan,Jiancheng Jiang 3

1 Introduction 3

2 Cox's type of models 4

3 Multivariate Cox's type of models 14

4 Model selection on Cox's models 24

5 Validating Cox's type of models 27

6 Transformation models 28

7 Concluding remarks 30

References 30

Chapter 2 Additive-Accelerated Rate Model for Recurrent Event Donglin Zeng,Jianwen Cai 35

1 Introduction 35

2 Inference procedure and asymptotic properties 37

3 Assessing additive and accelerated covariates 40

4 Simulation studies 41

5 Application 42

6 Remarks 43

Acknowledgements 44

Appendix 44

References 48

Chapter 3 An Overview on Quadratic Inference Function Approaches for Longitudinal Data John J.Dziak,Runze Li,Annie Qu 49

1 Introduction 49

2 The quadratic inference function approach 51

3 Penalized quadratic inference function 56

4 Some applications of QIF 60

5 Further research and concluding remarks 65

Acknowledgements 68

References 68

Chapter 4 Modeling and Analysis of Spatially Correlated Data Yi Li 73

1 Introduction 73

2 Basic concepts of spatial process 76

3 Spatial models for non-normal/discrete data 82

4 Spatial models for censored outcome data 88

5 Concluding remarks 96

References 96

Part Ⅱ Statistical Methods for Epidemiology 103

Chapter 5 Study Designs for Biomarker-Based Treatment Selection Amy Laird,Xiao-Hua Zhou 103

1 Introduction 103

2 Definition of study designs 104

3 Test of hypotheses and sample size calculation 108

4 Sample size calculation 111

5 Numerical comparisons of efficiency 116

6 Conclusions 118

Acknowledgements 121

Appendix 122

References 126

Chapter 6 Statistical Methods for Analyzing Two-Phase Studies Jinbo Chen 127

1 Introduction 127

2 Two-phase case-control or cross-sectional studies 130

3 Two-phase designs in cohort studies 136

4 Conclusions 149

References 151

Part Ⅲ Bioinformatics 159

Chapter 7 Protein Interaction Predictions from Diverse Sources Yin Liu,Inyoung Kim,Hongyu Zhao 159

1 Introduction 159

2 Data sources useful for protein interaction predictions 161

3 Domain-based methods 163

4 Classification methods 169

5 Complex detection methods 172

6 Conclusions 175

Acknowledgements 175

References 175

Chapter 8 Regulatory Motif Discovery:From Decoding to Meta-Analysis Qing Zhou,Mayetri Gupta 179

1 Introduction 179

2 A Bayesian approach to motif discovery 181

3 Discovery of regulatory modules 184

4 Motif discovery in multiple species 189

5 Motif learning on ChIP-chip data 195

6 Using nucleosome positioning information in motif discovery 201

7 Conclusion 204

References 205

Chapter 9 Analysis of Cancer Genome Alterations Using Single Nucleotide Polymorphism(SNP)Microarrays Cheng Li,Samir Amin 209

1 Background 209

2 Loss of heterozygosity analysis using SNP arrays 212

3 Copy number analysis using SNP arrays 216

4 High-level analysis using LOH and copy number data 224

5 Software for cancer alteration analysis using SNP arrays 229

6 Prospects 231

Acknowledgements 231

References 231

Chapter 10 Analysis of ChIP-chip Data on Genome Tiling Microarrays W.Evan Johnson,Jun S.Liu,X.Shirley Liu 239

1 Background molecular biology 239

2 A ChIP-chip experiment 241

3 Data description and analysis 244

4 Follow-up analysis 249

5 Conclusion 254

References 254

Subject Index 259

Author Index 261