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Statistical Models of Treatment Eff
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ISBN: 978-90-8559-069-9 © Bettina
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PROMOTIECOMMISSIE Promotor: Prof.dr
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CONTENTS Chapter 1. Introduction 11
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Cha pter 1 Introduction
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Chapter 1 14 Epidemiology Worldwide
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Chapter 1 16 Prediction models with
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Chapter 1 18 standard method fails
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Chapter 1 20 The extended non-linea
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Chapter 1 22 References 1. Blumberg
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Cha pter 2 Prediction of response t
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Chapter 2.1 28 ABSTRACT The aim of
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Chapter 2.1 30 been hepatitis B sur
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Chapter 2.1 32 HBV DNA decline The
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Chapter 2.1 34 Figure 2 continued.
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Chapter 2.1 36 Figure 4. Estimated
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Chapter 2.1 38 DNA was observed in
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Chapter 2.1 40 15. Kao JH. Role of
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Chapter 2.2 44 ABSTRACT Background:
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Chapter 2.2 46 low baseline HBV DNA
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Chapter 2.2 48 patient subgroups wa
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Chapter 2.2 50 p=0.002). Previous I
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Chapter 2.2 52 Application of the m
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Chapter 2.2 54 PEG-IFN, the proport
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Chapter 2.2 56 References 1. Lavanc
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Chapter 2.2 58 26. Bonino F, Lau GK
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Chap ter 2.3 Prediction of the resp
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INTRODUCTION Dynamic prediction of
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Statistical analysis Dynamic predic
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Dynamic prediction of response to P
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Dynamic prediction of response to P
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Dynamic prediction of response to P
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Dynamic prediction of response to P
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References Dynamic prediction of re
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Cha pter 2.4 Dynamic prediction of
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INTRODUCTION Dynamic prediction of
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For the indirect approach we rewrit
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logit pi,j = logit Pr(Ri =1|visit =
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Dynamic prediction of response usin
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Dynamic prediction of response usin
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Dynamic prediction of response usin
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Dynamic prediction of response usin
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Dynamic prediction of response usin
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Dynamic prediction of response usin
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Table 1. Results of different stopp
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Dynamic prediction of response usin
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Dynamic prediction of response usin
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Chapter 2.5 106 ABSTRACT Peginterfe
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Chapter 2.5 108 and placebo daily.
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Chapter 2.5 110 for patients with a
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Chapter 2.5 112 Mean HBV DNA declin
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Chapter 2.5 114 peginterferon and n
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Chapter 2.5 116 hepatocellular carc
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Chapter 2.5 118 13. Werle-Lapostoll
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Chapter 2.5 120 Greece - G Germanid
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Chap ter 3.1 Long-term clinical out
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INTRODUCTION Glycyrrhizin for IFN-n
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Statistics Glycyrrhizin for IFN-non
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Glycyrrhizin for IFN-non responders
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Table 2. Time dependent Cox regress
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Glycyrrhizin for IFN-non responders
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Glycyrrhizin for IFN-non responders
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- Page 145 and 146: Introduction Discriminant analysis
- Page 147 and 148: Discriminant analysis using a MLMM
- Page 149 and 150: Estimation Discriminant analysis us
- Page 151 and 152: Discriminant analysis using a MLMM
- Page 153 and 154: where wi,k(y i, θ) = (k =1,...,K).
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- Page 171 and 172: Appendix Discriminant analysis usin
- Page 175: Cha pter 4 Statistical models of ea
- Page 178 and 179: Chapter 4.1 176 ABSTRACT Nucleoside
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- Page 186 and 187: Chapter 4.1 184 Figure 1. Viral dec
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- Page 194 and 195: Chapter 4.2 192 ABSTRACT Tenofovir,
- Page 196 and 197: Chapter 4.2 194 PATIENTS AND METHOD
- Page 198 and 199: Chapter 4.2 196 2 Slow: decline bet
- Page 200 and 201: Chapter 4.2 198 Table 2. Parameter
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- Page 204 and 205: Chapter 4.2 202 release. Although w
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- Page 212 and 213: Chapter 4.3 210 ABSTRACT Treatment
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- Page 216 and 217: Chapter 4.3 214 The resulting model
- Page 218 and 219: Chapter 4.3 216 Figure 1. Median HB
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- Page 224 and 225: Chapter 4.3 222 13-14 This model ta
- Page 226 and 227: Chapter 4.3 224 References 1. Kane
- Page 228 and 229: Chapter 4.3 226 25. Wolters LM, Han
- Page 231: Cha pter 5 Summary and conclusion
- Page 234 and 235: Summary and conclusion 232 Therapy
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Samenvatting en conclusie 242 posit
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Samenvatting en conclusie 244 De ve
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Samenvatting en conclusie 246 en na
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Samenvatting en conclusie 248 In ee
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DANKWOORD Dankwoord 253 Met oplucht
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CUR RICULUM VITAE Curriculum Vitae
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Bibliography 258 Mechanical factors
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Bibliography 260 35. Wolters LM, Ha
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Bibliography 262 Volume Measurement
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Bibliography 264 Quantitative HBV D
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Bibliography 266 to Peginterferon-a
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ISBN: 978-90-8559-069-9