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Titlebook: New Frontiers of Biostatistics and Bioinformatics; Yichuan Zhao,Ding-Geng Chen Book 2018 Springer Nature Switzerland AG 2018 Biostatistica

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发表于 2025-3-21 18:01:21 | 显示全部楼层 |阅读模式
书目名称New Frontiers of Biostatistics and Bioinformatics
编辑Yichuan Zhao,Ding-Geng Chen
视频video
概述Features 22 contributions from the 5th Workshop on Biostatistics and Bioinformatics.Features contributions on topics such as fMRI data analysis, survival analysis, longitudinal data analysis, Bayesian
丛书名称ICSA Book Series in Statistics
图书封面Titlebook: New Frontiers of Biostatistics and Bioinformatics;  Yichuan Zhao,Ding-Geng Chen Book 2018 Springer Nature Switzerland AG 2018 Biostatistica
描述.This book is comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017. Featuring twenty-two selected papers from the workshop, this book showcases the most current advances in the field, presenting new methods, theories, and case applications at the frontiers of biostatistics, bioinformatics, and interdisciplinary areas..Biostatistics and bioinformatics have been playing a key role in statistics and other scientific research fields in recent years. The goal of the 5th Workshop on Biostatistics and Bioinformatics was to stimulate research, foster interaction among researchers in field, and offer opportunities for learning and facilitating research collaborations in the era of big data. The resulting volume offers timely insights for researchers, students, and industry practitioners. .
出版日期Book 2018
关键词Biostatistical Procedures; Adaptive Design; High Dimensional Statistical Method; Multivariate Survival
版次1
doihttps://doi.org/10.1007/978-3-319-99389-8
isbn_ebook978-3-319-99389-8Series ISSN 2199-0980 Series E-ISSN 2199-0999
issn_series 2199-0980
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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Optimal Weighted Wilcoxon–Mann–Whitney Test for Prioritized Outcomestatistic that maximize its power. We provide the rationale for the weights and their implications in the application of the method. In addition, we derive a formula for its power and demonstrate its accuracy in simulations. Finally, we apply the method to data from an acute ischemic stroke clinical trial of normobaric oxygen therapy.
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Statistical Modeling for the Heart Disease Diagnosis via Multiple Imputationce of multiple imputation is widely accepted as a less biased and more valid result. In the chapter, we apply the multiple imputation to a public-accessible heart disease dataset, which has a high missing rate, and build a prediction model for the heart disease diagnosis.
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Rank-Based Empirical Likelihood for Regression Models with Responses Missing at Random distributions with different response probabilities are considered. The simulation results show that the proposed approach has better performance for the regression parameters compared to the normal approximation approach and its least-squares counterpart. Finally, a data example is provided to illustrate our method.
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Wavelet-Based Profile Monitoring Using Order-Thresholding Recursive CUSUM Schemes of multiple wavelet coefficients. Extensive simulation studies and a case study of tonnage profile data demonstrate that our proposed procedure is efficient for detecting the unknown local changes on the profile.
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Mammogram Diagnostics Using Robust Wavelet-Based Estimator of Hurst Exponentally and numerically. Compared with other standard wavelet-based methods (Veitch and Abry (VA) method, Soltani, Simard, and Boichu (SSB) method, median based estimators MEDL and MEDLA, and Theil-type (TT) weighted regression method), our methods reduce the variance of the estimators and increase the
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