New Advances in Statistics and Data Science

Part 1 Review and Theoretical Framework in Data Science.- Ch 1 Statistical Distances and Their Role in Robustness.- Ch 2 The Out-source Error in Multi-source Cross Validation-type Procedures.- Ch 3.- Meta-Analysis for Rare Events as Binary Outcomes.- Ch 4 New Challenges and Strategies in Robust Optimal Design for Multicategory Logit Modelling.- Ch 5 Testing of Multivariate Spline Growth Model.- Part 2 Complex and Big Data Analysis.- Ch 6 Uncertainty Quantification Using the Neighbor Gaussian Process.- Ch 7 Tuning Parameter Selection in the LASSO with Unspecified Propensity.- Adaptive Filtering Increases Power to Detect Differently Expressed Genes.- Ch 9 Estimating Parameters in Complex Systems with Functional Outputs - A Wavelet-based Approximate Bayesian Computation Approach.- Ch 10 A maximum Likelihood Approach for Non-invasive Cancer Diagnosis Using Methylation Profiling of Cell-free DNA from Blood.- Part 3 Clinical Trials, Statistical Shape Analysis and Application.- Ch 11 A Simpleand Efficient Statistical Approach for Designing an Early Phase II Clinical Trial - Ordinal Linear Contrast Test.- Ch 12 Landmark-constrained Statistical Shape Analysis of Elastic Curves and Surfaces.- Ch 13 Phylogeny-based kernels with Application to Microbiome Association Studies.- Ch 14 Accounting for Differential Error in Time-to-event Analyses using Imperfect Electronic Health Record-derived Endpoints.- Part 4 Statistical Modeling and Data Analysis.- Ch 15 Modeling Inter-trade Durations in the Limit Order market.- Ch 16 Assessment of Drug Interactions with Repeated Measurements.- Ch 17 Statistical Indices for Risk Tracking in Longitudinal Studies.- Ch 18 Statistical Analysis of Labor market Integration: A Mixture Regression Approach.- Ch 19 Bias Correction in Age-Cohort Models Using Eigen Analysis.

Ding-Geng Chen is a Fellow of the American Statistical Association and is currently the Wallace Kuralt distinguished professor at the University of North Carolina at Chapel Hill. He was a professor at the University of Rochester and the Karl E. Peace endowed eminent scholar chair in biostatistics at Georgia Southern University. He is also a senior statistics consultant for biopharmaceuticals and government agencies with extensive expertise in Monte-Carlo simulations, clinical trial biostatistics and public health statistics. Professor Chen has more than 100 referred professional publications, has co-authored and co-edited six books on clinical trial methodology, meta-analysis and public health applications, and has been invited nationally and internationally to give speeches on his research. Professor Chen was honored with the "Award of Recognition" in 2014 by the Deming Conference Committee for highly successful advanced biostatistics workshop tutorials with his books.



Zhezhen Jin is a Professor of Biostatistics at Columbia University. His research interests in statistics include survival analysis, resampling methods, longitudinal data analysis, and nonparametric and semiparametric models. Dr. Jin has collaborated on research in the areas of cardiology, neurology, hematology, oncology and epidemiology. He is a founding editor-in-chief of Contemporary Clinical Trials Communications, serves as an associate editor for Lifetime Data Analysis, Contemporary Clinical Trials, and Communications for Statistical Applications and Methods, and is on the editorial board for Kidney International, the Journal of the International Society for Nephrology. Dr. Jin has published over 150 peer-reviewed research papers in statistical and medical journals, and is also a Fellow of the American Statistical Association.



Gang Li is a Professor of Biostatistics and Biomathematics at the University of Californiaat Los Angeles (UCLA)