Advanced Medical Statistics by Ying Lu

Advanced Medical Statistics

byYing Lu, Jiqian Fang, Lu Tian;Hua Jin

Kobo ebook | June 29, 2015

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The book aims to provide both comprehensive reviews of the classical methods and an introduction to new developments in medical statistics. The topics range from meta analysis, clinical trial design, causal inference, personalized medicine to machine learning and next generation sequence analysis. Since the publication of the first edition, there have been tremendous advances in biostatistics and bioinformatics. The new edition tries to cover as many important emerging areas and reflect as much progress as possible. Many distinguished scholars, who greatly advanced their research areas in statistical methodology as well as practical applications, also have revised several chapters with relevant updates and written new ones from scratch.

The new edition has been divided into four sections, including, Statistical Methods in Medicine and Epidemiology, Statistical Methods in Clinical Trials, Statistical Genetics, and General Methods. To reflect the rise of modern statistical genetics as one of the most fertile research areas since the publication of the first edition, the brand new section on Statistical Genetics includes entirely new chapters reflecting the state of the art in the field.

Although tightly related, all the book chapters are self-contained and can be read independently. The book chapters intend to provide a convenient launch pad for readers interested in learning a specific topic, applying the related statistical methods in their scientific research and seeking the newest references for in-depth research.


  • Statistics in Medicine and Epidemiology:

    • History of Statistical Thinking in Medicine (Tar Timothy Chen)
    • Describing Data, Modeling Variation, and Statistical Practice (Hongyan Du and Ming T Tan)
    • Covariate-Specific and Covariate-Adjusted Predictive Values of Prognostic Biomarkers with Survival Outcome (Yunbei Ma, Xiao-Hua Zhou and Kwun Chuen (Gary) Chan)
    • Statistical Methods for Personalized Medicine (Lu Tian and Xiaoguang Zhao)
    • Statistics Used in Quality Control, Quality Assurance, and Quality Improvement in Radiological Studies (Ying Lu and Shoujun Zhao)
    • Applications of Statistical Methods in Medical Imaging (Jesse S Jin)
    • Cost-Effectiveness Analysis and Evidence-Based Medicine (Jianli Li)
    • Quality of Life: Issues Concerning Assessment and Analysis (Jiqian Fang and Yuantao Hao)
    • Meta-Analysis (Xuyu Zhou, Jiqian Fang, Chuanhua Yu, Zongli Xu, Lu Tian, and Ying Lu)
    • Statistical Models and Methods in Infectious Diseases (Hulin Wu and Shoujun Zhao)
    • Special Models for Sampling Survey (Sujuan Gao)
    • The Use of Capture–Recapture Methodology in Epidemiological Surveillance and Ecological Surveys (Anne Chao, T C Hsieh and Hsin-Chou Yang)
    • Statistical Methods in the Effective Evaluation of Mass Screening for Diseases (Qing Liu)
  • Statistics in Clinical Trials:

    • Statistics in Biopharmaceutical Research and Development (Shein-Chung Chow and Annpey Pong)
    • Statistics in Pharmacology and Pre-Clinical Studies (Tze Leung Lai, Mei-Chiung Shin and Guangrui Zhu)
    • Statistics in Toxicology (James J Chen)
    • Dose-Response Modeling and Benchmark Doses in Health Risk Assessment (Yiliang Zhu)
    • Some Fundamental Statistical Issues and Methodologies in Confirmatory Trials (George Y H Chi, Haiyan Xu and Qing Liu)
    • Surrogates for Qualitative Evaluation of Treatment Effects (Zhi Geng)
    • Adaptive Trial Design in Clinical Research (Annpey Pong and Shein-Chung Chow)
    • Statistics in the Research of Traditional Chinese Medicine (Danhui Yi and Yang Li)
  • Statistical Genetics:

    • Sparse Segment Identifications with Applications to DNA Copy Number Variation Analysis (X Jessie Jeng, T Tony Cai and Hongzhe Li)
    • Statistical Methods for Design and Analysis of Linkage Studies (Qizhai Li, Hong Qin, Zhaohai Li, and Gang Zheng)
    • Transcriptome Analysis Using Next-Generation Sequencing (Jingyi Jessica Li, Haiyan Huang, Minping Qian and Xuegong Zhang)
    • Genetic Structure of Human Population (Hua Tang and Kun Tang)
    • Data Integration Methods in Genome Wide Association Studies (Ning Sun and Hongyu Zhao)
    • Causal Inference (Zhi Geng)
  • General Methods:

    • Survival Analysis (D Y Lin)
    • Nonparametric Regression Models for the Analysis of Longitudinal Data (Colin O Wu, Xin Tian, Kai F Yu, and Mi-Xia Wu)
    • Local Modeling: Density Estimation and Nonparametric Regression (Jianqing Fan and Runze Li)
    • Statistical Methods for Dependent Data (Feng Chen)
    • Bayesian Methods (Ming-Hui Chen and Keying Ye)
    • Valid Prior-Free Probabilistic Inference and Its Applications in Medical Statistics (Duncan Ermini Leaf, Hyokun Yun, and Chuanhai Liu)
    • Stochastic Processes and Their Applications in Medical Science (Caixia Li and Jiqian Fang)
    • Interpolation of Missing Values and Adjustment of Moving Holiday Effect in Time Series (Zhang Jin-Xin, Zhang Xi, Xue Yun-Lian, Li Ji-Bin and Huang Bo)
    • Tree-based Methods (Heping Zhang)
    • Introduction to Artificial Neural Networks (Xia Jielai, Jiang Hongwei, and Tang Qiyi)

Readership: Biostatisticians, applied statisticians, medical researchers and clinicians, biopharmaceutical researchers, public health epidemiologists, biometricians and applied mathematicians.
Key Features:

  • The book covers very broad topics in medical statistics
  • The book covers both most recent developments as well as classical work of the selected areas
  • The book chapter is written by the experts in the field and illustrated with real life examples
Title:Advanced Medical StatisticsFormat:Kobo ebookPublished:June 29, 2015Publisher:World Scientific Publishing CompanyLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:9814583324

ISBN - 13:9789814583329