Multiple Comparisons Using R (eBook, PDF) - Bretz, Frank; Hothorn, Torsten; Westfall, Peter
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  • Format: PDF

Controlling multiplicity in experiments ensures better decision making and safeguards against false claims. Adopting a unifying theme based on maximum statistics, this self-contained introduction describes the common underlying theory of multiple comparison procedures through numerous examples. It covers a range of multiple comparison procedures, from the Bonferroni method and Simes' test to resampling and adaptive design methods. The book also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org…mehr

Produktbeschreibung
Controlling multiplicity in experiments ensures better decision making and safeguards against false claims. Adopting a unifying theme based on maximum statistics, this self-contained introduction describes the common underlying theory of multiple comparison procedures through numerous examples. It covers a range of multiple comparison procedures, from the Bonferroni method and Simes' test to resampling and adaptive design methods. The book also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org

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Autorenporträt
Frank Bretz is Global Head of the Statistical Methodology group at Novartis Pharma AG in Basel, Switzerland. He is also an adjunct professor at the Hannover Medical School in Germany.

Torsten Hothorn is a professor of biostatistics in the Faculty of Mathematics, Computer Science and Statistics at Ludwig-Maximilians-Universit¿Munchen in Germany.

Peter Westfall is James and Marguerite Niver and Paul Whitfield Horn Professor of Statistics and associate director of the Center for Advanced Analytics and Business Intelligence at Texas Tech University in Lubbock, USA.