This monograph offers an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate and related error measures, particularly addressing applications to such fields as genetics, proteomics and neuroscience.

This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.

Concise treatment of theoretical and practical properties of the false discovery rate (FDR) Detailed examples from the life sciences, accompanied by software solutions Includes latest developments of simultaneous statistical inference methods for a variety of non-standard situations Includes supplementary material: sn.pub/extras

Autorentext

Thorsten Dickhaus has been a Full Professor of Mathematical Statistics at the University of Bremen, Germany since 2015. He obtained his PhD in mathematics from the Heinrich Heine University, Düsseldorf, Germany in 2008 and held postdoc positions at the German Diabetes Center, Düsseldorf, and the Berlin Institute of Technology. He was a Junior Professor of Mathematical Statistics at the Humboldt University of Berlin. His research interests include multiple testing, asymptotic statistics, the theory of nonparametric tests, resampling and bootstrap techniques, statistical applications in the life sciences, and computational statistics.

Inhalt
The problem of simultaneous inference.- Part I General Theory.- Some theory of p-values.- Classes of multiple test procedures.- Simultaneous test procedures.- Stepwise rejective multiple tests.- Multiple testing and binary classification.- Multiple testing and model selection.- Software solutions for multiple hypotheses testing.- Part II From Genotype to Phenotype.- Genetic association studies.- Gene expression analyses.- Functional magnetic resonance imaging.- Part III Further Applications in the Life Sciences.- Further life science applications.