Quantitative Methods for HIV/AIDS Research
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Quantitative Methods in HIV/AIDS Research provides a comprehensive discussion of modern statistical approaches for the analysis of HIV/AIDS data. The first section focuses on statistical issues in clinical trials and epidemiology that are unique to or particularly challenging in HIV/AIDS research; the second section focuses on the analysis of laboratory data used for immune monitoring, biomarker discovery and vaccine development; the final section focuses on statistical issues in the mathematical modeling of HIV/AIDS pathogenesis, treatment and epidemiology.
This book brings together a broad perspective of new quantitative methods in HIV/AIDS research, contributed by statisticians and mathematicians immersed in HIV research, many of whom are current or previous leaders of CFAR quantitative cores. It is the editors’ hope that the work will inspire more statisticians, mathematicians and computer scientists to collaborate and contribute to the interdisciplinary challenges of understanding and addressing the AIDS pandemic.
Section I Quantitative Methods for Clinical Trials and Epidemiology
1. Statistical Issues in HIV Non-Inferiority Trials Mimi Kim
2. Sample Size for HIV-1 Vaccine Clinical Trials with Extremely Low Incidence Rate Shein-Chung Chow, Yuanyuan Kong, and Shih-Ting Chiu
3. Adaptive Clinical Trial Design Shein-Chung Chow and Fuyu Song
4. Generalizing Evidence from HIV Trials Using Inverse Probability of Sampling Weights Ashley L. Buchanan, Michael G. Hudgens, and Stephen R. Cole
5. Statistical Tests of Regularity among Groups with HIV Self-Test Data John Rice, Robert L. Strawderman, and Brent A. Johnson
Section II Quantitative Methods for Analysis of Laboratory Assays
6. Estimating Partial Correlations between Logged HIV RNA Measurements Subject to Detection Limits Robert H. Lyles
7. Quantitative Methods and Bayesian Models for Flow Cytometry Analysis in HIV/AIDS Research Lin Lin and Cliburn Chan
8. The Immunoglobulin Variable-Region Gene Repertoire and Its Analysis Thomas B. Kepler and Kaitlin Sawatzkiix
9. Probability-Scale Residuals in HIV/AIDS Research: Diagnostics and Inference Bryan E. Shepherd, Qi Liu, Valentine Wanga, Chun Li
Section III Quantitative Methods for Dynamical Models and Computer Simulations
10. Simulation Modeling of HIV Infection—From Individuals to Risk Groups and Entire Populations Georgiy Bobashev
11. Review of Statistical Methods for Within-Host HIV Dynamics in AIDS Studies Ningtao Wang and Hulin Wu
12. Precision in the Specification of Ordinary Differential Equations and Parameter Estimation in Modeling Biological Processes
Sarah E. Holte and Yajun Mei
"The book highlights statistical and mathematical work done in the quantitative cores of the Centers for AIDS Research (CFARs), a network of centers funded by the US National Institutes of Health, and gives a good sense of the breadth of quantitative issues involved in the varied research streams in HIV/AIDS. The level of the text varies between introductory overview and cutting-edge; some sections will be more useful for beginners in that area, others for experienced professionals with a challenging problem. Even having worked in HIV research for the bulk of my career, I learned something; simultaneously, I expect that someone new to the area would find it a useful introduction."
~Nicole Bohme Carnegie, Montana State University
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