This book establishes the theoretical foundations of a general methodology for multiple hypothesis testing and discusses its software implementation in R and SAS. These are applied to a range of problems in biomedical and genomic research, including identification of differentially expressed and co-expressed genes in high-throughput gene expression experiments; tests of association between gene expression measures and biological annotation metadata; sequence analysis; and genetic mapping of complex traits using single nucleotide polymorphisms. The procedures are based on a test statistics...
This book establishes the theoretical foundations of a general methodology for multiple hypothesis testing and discusses its software implementatio...
During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, sociology, and economics among many others, which involve collection of large amounts of data on subjects or organisms over time. The goal of such studies can be formulated as estimation of a finite dimensional parameter of the population distribution corresponding to the observed time-dependent process. Such estimation problems arise in...
During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex ob...
The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hundreds of thousands of measurements for a single subject. The field is ready to move towards clear objective benchmarks under which tools can be evaluated. Targeted learning allows (1) the full generalization and utilization of cross-validation as an estimator selection tool so that the subjective choices made by humans are now made by the machine, and (2) targeting the fitting of the probability distribution of the data toward the...
The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often ...
This textbook for Masters and PhD graduate students in biostatistics, statistics, data science, and epidemiology deals with the practical challenges that come with big, complex, and dynamic data while maintaining a strong theoretical foundation.
This textbook for Masters and PhD graduate students in biostatistics, statistics, data science, and epidemiology deals with the practical challenges...
