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" Contemporary Biostatistics with Biopharmaceutical Applications / "
Lanju Zhang, Ding-Geng (Din) Chen, Hongmei Jiang, Gang Li, Hui Quan, editors.
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BL
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| Record Number
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861357
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| Title & Author
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Contemporary Biostatistics with Biopharmaceutical Applications /\ Lanju Zhang, Ding-Geng (Din) Chen, Hongmei Jiang, Gang Li, Hui Quan, editors.
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| Publication Statement
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Cham :: Springer,, 2019.
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| Series Statement
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ICSA Book Series in Statistics Ser.
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1 online resource (339 pages)
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| ISBN
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303015310X
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: 9783030153106
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3030153096
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9783030153090
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| Notes
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6 Maximin Designs for Ultra-Fast Functional Brain Imaging
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| Contents
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Intro; Preface; Contents; Part I Biostatistical Methodology; 1 Nonparametric Inference on Tumor Incidence with Partially Identified Cause-of-Death Data; 1.1 Introduction; 1.2 Methods; 1.2.1 Data Structure; 1.2.2 Nonparametric Estimation; 1.2.3 A Class of K-Sample Logrank-Type Tests; 1.3 Simulation Studies; 1.4 A Pituitary Tumor Study; 1.5 Concluding Remarks; Supplementary Materials; References; 2 Variable Selection for High Dimensional Metagenomic Data; 2.1 Introduction; 2.2 Methods; 2.2.1 Metagenomic Data; 2.2.2 Linear Log-Contrast Model; 2.2.3 Proposed Method; 2.3 Simulation Studies
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2.3.1 Simulation Setting for Linear Regression Model2.3.2 Simulation Results; 2.4 Real Data Analysis; 2.5 Discussion and Future Work; References; 3 Dimension Reduction in High Dimensional Multivariate Time Series Analysis; 3.1 Introduction; 3.2 Existing Methods; 3.2.1 Regularization Methods; 3.2.1.1 The Lasso Method; 3.2.1.2 The Lag-Weighted Lasso Method; 3.2.1.3 The Hierarchical Vector Autoregression (HVAR) Method; 3.2.2 The Space-Time AR (STAR) Model; 3.2.3 Model-Based Clustering; 3.2.4 Factor Analysis; 3.3 Proposed Method for High Dimension Reduction; 3.4 Simulation Studies
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3.4.1 Scenario 13.4.2 Scenario 2; 3.4.3 Scenario 3; 3.5 Empirical Examples; 3.5.1 The Macroeconomic Time Series; 3.5.2 The Sexually Transmitted Disease Data; 3.6 Concluding Remarks; A.1 Appendix; References; 4 A Powerful Retrospective Multiple Variant Association Test for Quantitative Traits by Borrowing Strength from Complex Genotypic Correlations; 4.1 Introduction; 4.2 Methods; 4.2.1 Retrospective, Fixed-Weight Burden Test; 4.2.2 Adaptive-Weight Burden Test to Maximize Test Statistic; 4.2.3 Principal-Component-Based Adaptive-Weight Burden Test to Enhance Power; 4.2.4 Simulation Studies
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4.2.5 The NHLBI GO-ESP Data4.3 Results; 4.3.1 Assessment of Type I Error; 4.3.2 Power Comparison to Other Burden Tests; 4.3.3 Analysis of Rare Variant Association in GO-ESP Data; 4.4 Discussion; Appendix 1: Description of MASTOR and Theoretical Justification of the Null Distribution of SABT; Appendix 2: Additional Simulation Results Show That the Data-Driven Weights W* Is Adaptive to the Direction of True Genetic Effects; Appendix 3: Additional Simulation Results Show the Relation Between the ABT Statistic and the famSKAT Statistic
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Appendix 4: Additional Simulation Results to Validate the Asymptotic Null Distribution of SPC-ABT via Permutation Based ApproachAppendix 5: Additional Simulation Results for Type I Error Evaluation; References; 5 Inference of Gene Regulatory Network Through Adaptive Dynamic Bayesian Network Modeling; 5.1 Background; 5.2 Methods; 5.2.1 Dynamic Bayesian Network Modeling; 5.2.2 Interpolation by a Parametric or Nonparametric Function; 5.3 Results and Discussion; 5.3.1 Real Data Analyses; 5.4 Computer Simulation; 5.4.1 Simulation Process; 5.4.2 Results; 5.5 Conclusions; References
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| Abstract
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This edited volume presents current research in biostatistics with emphasis on biopharmaceutical applications. Featuring contributions presented at the 2017 ICSA Applied Statistics Symposium held in Chicago, IL on June 25 to 28, 2017, this book explores timely topics that have a high potential impact on statistical methodology and future research in biostatistics and biopharmaceuticals. The theme of this conference was Statistics for A New Generation: Challenges and Opportunities, in recognition of the advent of a new generation of statisticians. The conference attracted statisticians working in academia, government, and industry; domestic and international statisticians. From the conference, the editors selected 28 high-quality presentations and invited the speakers to prepare full chapters for this book. These contributions are divided into four parts: Part I Biostatistical Methodology, Part II Statistical Genetics and Bioinformatics, Part III Regulatory Statistics, and Part IV Biopharmaceutical Research and Applications. Featuring contributions on topics such as statistics in genetics, bioinformatics, biostatistical methodology, and statistical computing, this book is beneficial to researchers, academics, practitioners and policy makers in biostatistics and biopharmaceuticals.
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Medical statistics.
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Medical statistics.
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| Dewey Classification
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519.5
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| LC Classification
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QA276-280QH323.5QA27
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RA409
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| Added Entry
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Chen, Ding-Geng (Din)
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Jiang, Hongmei.
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Li, Gang.
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Quan, Hui.
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Zhang, Lanju.
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