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Thedevelopmentoftechnologiesforhigh-throughputmeasurementofgene expression in biological system is providing powerful new tools for inv- tigating the transcriptome on a genomic scale, and across diverse biol- ical systems and experimental designs. This technological transformation is generating an increasing demand for data analysis in biological inv- tigations of gene expression. This book focuses on data analysis of gene expression microarrays. The goal is to provide guidance to practitioners in deciding which statistical approaches and packages may be indicated for their projects, in...

Thedevelopmentoftechnologiesforhigh-throughputmeasurementofgene expression in biological system is providing powerful new tools for inv- tigating the transcriptome on a genomic scale, and across diverse biol- ical systems and experimental designs. This technological transformation is generating an increasing demand for data analysis in biological inv- tigations of gene expression. This book focuses on data analysis of gene expression microarrays. The goal is to provide guidance to practitioners in deciding which statistical approaches and packages may be indicated for their projects, in...

Decision theory provides a formal framework for making logical choices in the face of uncertainty. Given a set of alternatives, a set of consequences, and a correspondence between those sets, decision theory offers conceptually simple procedures for choice. This book presents an overview of the fundamental concepts and outcomes of rational decision making under uncertainty, highlighting the implications for statistical practice.

The authors have developed a series of self contained chapters focusing on bridging the gaps between the different fields that have contributed to rational...

Medical decision making has evolved in recent years, as more complex problems are being faced and addressed based on increasingly large amounts of data. In parallel, advances in computing have led to a host of new and powerful statistical tools to support decision making. Simulation-based Bayesian methods are especially promising, as they provide a unified framework for data collection, inference, and decision making. In addition, these methods are simple to interpret, and can help to address the most pressing practical and ethical concerns arising in medical decision making.
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