Recent Advances In Biostatistics: False Discovery Rates, Survival Analysis, And Related Topics False Discovery Rates, Survival Analysis, and Related Topics

This study is based on the idea that Boltzmann-like modelling methods can be developed to design, with special attention to applied sciences, kinetic-type models which are called generalized kinetic models. In particular, these models appear in evolution equations for the statistical distribution over the physical state of each individual of a large population. The evolution is determined both by interactions among individuals and by external actions. Considering that generalized kinetic models can play an important role in dealing with several interesting systems in applied sciences, the book provides a unified presentation of this topic with direct reference to modelling, mathematical statement of problems, qualitative and computational analysis, and applications. Models reported and proposed in the book refer to several fields of natural, applied and technological sciences. In particular, the following classes of models are discussed: population dynamics and socio-economic behaviours; models of aggregation and fragmentation phenomena; models of biology and immunology; traffic flow models; models of mixtures; and particles undergoing classic and dissipative interactions This unique volume provides self-contained accounts of some recent trends in biostatistics methodology and their applications. It includes state-of-the-art reviews and original contributions. The articles included in this volume are based on a careful selection of peer-reviewed papers, authored by eminent experts in the field, representing a well balanced mix of researchers from the academia, R&D sectors of government and the pharmaceutical industry. The book is also intended to give advanced graduate students and new researchers a scholarly overview of several research frontiers in biostatistics, which they can use to further advance the field through development of new techniques and results. Read more... Pt. 1. False discovery rates -- pt. 2. Survival analysis -- pt. 3. Related topics : genomics/bioinformatics, medical imaging and diagnosis, clinical trials Pt. I. False discovery rates. 1. A new adaptive method to control the false discovery rate / Fang Liu and Sanat K. Sarkar. 2. Adaptive multiple testing procedures under positive dependence / Wenge Guo, Sanat K. Sarkar and Shyamal D. Peddada. 3. A false discovery rate procedure for categorical data / Joseph F. Heyse -- pt. II. Survival analysis. 4. Conditional Nelson-Aalen and Kaplan-Meier estimators with the Muller-Wang boundary kernel / Xiaodong Luo and Wei-Yann Tsai. 5. Regression analysis in failure time mixture models with change points according to thresholds of a covariate / Jimin Lee, Thomas H. Scheike and Yanqing Sun. 6. Modeling survival data using the piecewise exponential model with random time grid / Fabio N. Demarqui [und weitere]. 7. Proportional rate models for recurrent time event data under dependent censoring : A comparative study / Leila D.A.F Amorim, Jianwen Cai and Donglin Zeng. 8. Efficient algorithms for Bayesian binary regression model with skew-probit link / Rafael B.A. Farias and Marcia D. Branco. 9. M-estimation methods in heteroscedastic nonlinear regression models / Changwon Lim, Pranab K. Sen and Shyamal D. Peddada. 10. The inverse censoring weighted approach for estimation of survival functions from left and right censored data / Sundarraman Subramanian and Peixin Zhang. 11. Analysis and design of competing risks data in clinical research / Haesook T. Kim -- pt. III. Related topics : Genomics/bioinformatics, medical imaging and diagnosis, clinical trials. 12. Comparative genomic analysis using information theory / Sarosh N. Fatakia, Stefano Costanzi and Carson C. Chow. 13. Statistical modeling for data of positron emission tomography in depression / Chung Chang and R. Todd Ogden. 14. The use of latent class analysis in medical diagnosis / David Rindskopf. 15. Subset selection in comparative selection trials / Cheng-Shiun Leu, Ying Kuen Cheung and Bruce Levin This unique volume provides self-contained accounts of some recent trends in biostatistics methodology and their applications. It includes state-of-the-art reviews and original contributions. The articles included in this volume are based on a careful selection of peer-reviewed papers, authored by eminent experts in the field, representing a well balanced mix of researchers from the academia, R & D sectors of government and the pharmaceutical industry. The book is also intended to give advanced graduate students and new researchers a scholarly overview of several research frontiers in biostatistics, which they can use to further advance the field through development of new techniques and results