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Atanu Biswas, PhD, is Assistant Professor in the Applied Statistics Unit at the Indian Statistical Institute, Kolkata in India. Dr. Biswas has authored more than eighty published articles and also serves as Associate Editor of several journals, including Sequential Analysis and Communications in Statistics. He is the recipient of the M.N. Murthy Award for his research in applied statistics. Sujay Datta, PhD, is Associate Professor in the Department of Mathematics and Computer Science at Northern Michigan University and Visiting Research Scientist in the Department of Statistics at TexasA&M University, where he is part of a bioinformatics research program sponsored by the National Institutes of Health. Dr. Datta's research interests include high-throughput data, genomics, and models based on graphs/networks. Jason P. Fine, PhD, is Associate Professor in the Department of Statistics at the University of Wisconsin-Madison and also serves as Associate Editor of several journals, including Biometrics, Biostatistics, and the Scandinavian Journal of Statistics. Mark R. Segal, PhD, is Professor in the Department of Epidemiology and Biostatistics at the University of California, San Francisco. A Fellow of the American Statistical Association, Dr. Segal has published extensively and currently focuses his research in the area of bioinformatics.
| Clinical Trials | |
| Phase I Clinical Trials in Oncology | |
| Introduction | |
| Phase I Trials in Healthy Volunteers | |
| Phase I Trials With Toxic Outcomes Enrolling Patients | |
| Other Design Problems in Dose Finding | |
| Concluding Remarks | |
| References | |
| Phase II Clinical Trials | |
| Introduction | |
| Frequentist methods in phase II clinical trials | |
| Bayesian methods in phase II clinical trials | |
| Decision theoretic methods in phase II clinical trials | |
| Clinical trials combining phases II and III | |
| Outstanding issues in phase II clinical trials | |
| References | |
| Response Adaptive Designs in Phase III Clinical Trials | |
| Introduction | |
| Adaptive Designs for Binary Treatment Responses Incorporating Covariates | |
| Adaptive Designs for Categorical Responses | |
| Adaptive Designs for Continuous Responses | |
| Optimal Adaptive Designs | |
| Delayed Responses in Adaptive Designs | |
| Biased Coin Designs | |
| Real Adaptive Clinical Trials | |
| Data Study for Different Adaptive Scheme | |
| Concluding Remarks | |
| References | |
| Inverse Sampling for Clinical Trials: A Brief Review of Theory and Practice | |
| Introduction | |
| Two-Sample Randomized Inverse Sampling for Clinical Trials | |
| An Example of Inverse Sampling: Boston ECMO | |
| Inverse Sampling in Adaptive Designs | |
| Concluding | |
| The Design and Analysis Aspects of Cluster Randomized Trials | |
| Introduction: Cluster Randomized Trials | |
| Intra-Cluster Correlation Coefficient and Confidence Interval | |
| Sample Size Calculation for Cluster Randomized Trials | |
| Analysis of Cluster Randomized Trial Data | |
| Concluding Remarks | |
| References | |
| Epidemiology | |
| HIV Dynamics Modeling and Prediction of Clinical Outcomes in AIDS Clinical Research | |
| Introduction | |
| HIV Dynamic Model and Treatment Effects Models | |
| Statistical Methods for Predictions of Clinical Outcomes | |
| Simulation Study | |
| Clinical Data Analysis | |
| Concluding Remarks | |
| References | |
| Spatial Epidemiology | |
| Space and Disease | |
| Basic Spatial Questions and Related Data | |
| Quantifying Pattern in Point Data | |
| Predicting Spatial Observations | |
| Concluding Remarks | |
| References | |
| Modeling Disease Dynamics: Cholera as a Case Study | |
| Introduction | |
| Data Analysis via Population Models | |
| Sequential Monte Carlo | |
| Modeling Cholera | |
| Concluding Remarks | |
| References | |
| Misclassification and Measurement Error Models in Epidemiological Studies | |
| Introduction | |
| A Few Examples | |
| Binary Regression Models with Two Types of Errors | |
| Bivariate Binary Regression Models with Two Types of Errors | |
| Models for Analyzing Mixed Misclassified Binary and Continuous Responses | |
| Atom Bomb Data Analysis | |
| Concluding Remarks | |
| References | |
| Survival Analysis | |
| Semiparametric Maximum Likelihood Inference in Survival Analysis | |
| Introduction | |
| Examples of Survival Models | |
| Basic Estimation and Limit Theory | |
| Table of Contents provided by Publisher. All Rights Reserved. |
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