Recent Developments in Multiple Comparison Procedures

Recent Developments in Multiple Comparison Procedures PDF Author: Yoav Benjamini
Publisher: IMS
ISBN: 9780940600638
Category : Mathematics
Languages : en
Pages : 168

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Book Description

Recent Developments in Multiple Comparison Procedures

Recent Developments in Multiple Comparison Procedures PDF Author: Yoav Benjamini
Publisher: IMS
ISBN: 9780940600638
Category : Mathematics
Languages : en
Pages : 168

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Book Description


Multiple Comparison Procedures

Multiple Comparison Procedures PDF Author: Larry E. Toothaker
Publisher: SAGE
ISBN: 9780803941779
Category : Mathematics
Languages : en
Pages : 108

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Book Description
If you conduct research with more than two groups and want to find out if they are significantly different when compared two at a time, then you need Multiple Comparison Procedures. Using examples to illustrate major concepts, this concise volume is your guide to multiple comparisons. Toothaker thoroughly explains such essential issues as planned vs. post-hoc comparisons, stepwise vs. simultaneous test procedures, types of error rate, unequal sample sizes and variances, and interaction tests vs. cell mean tests.

Applied Statistics in Agricultural, Biological, and Environmental Sciences

Applied Statistics in Agricultural, Biological, and Environmental Sciences PDF Author: Barry Glaz
Publisher: John Wiley & Sons
ISBN: 0891183590
Category : Technology & Engineering
Languages : en
Pages : 672

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Book Description
Better experimental design and statistical analysis make for more robust science. A thorough understanding of modern statistical methods can mean the difference between discovering and missing crucial results and conclusions in your research, and can shape the course of your entire research career. With Applied Statistics, Barry Glaz and Kathleen M. Yeater have worked with a team of expert authors to create a comprehensive text for graduate students and practicing scientists in the agricultural, biological, and environmental sciences. The contributors cover fundamental concepts and methodologies of experimental design and analysis, and also delve into advanced statistical topics, all explored by analyzing real agronomic data with practical and creative approaches using available software tools. IN PRESS! This book is being published according to the “Just Published” model, with more chapters to be published online as they are completed.

Statistical Analysis of Designed Experiments

Statistical Analysis of Designed Experiments PDF Author: Ajit C. Tamhane
Publisher: John Wiley & Sons
ISBN: 1118491432
Category : Science
Languages : en
Pages : 724

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Book Description
A indispensable guide to understanding and designing modern experiments The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences. The book supplies a foundation for the subject, beginning with basic concepts of DOE and a review of elementary normal theory statistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in a comprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for its analysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesis tests. Numerous theoretical and applied exercises are provided in each chapter, and answers to selected exercises are included at the end of the book. An appendix features three case studies that illustrate the challenges often encountered in real-world experiments, such as randomization, unbalanced data, and outliers. Minitab® software is used to perform analyses throughout the book, and an accompanying FTP site houses additional exercises and data sets. With its breadth of real-world examples and accessible treatment of both theory and applications, Statistical Analysis of Designed Experiments is a valuable book for experimental design courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge of DOE.

Multiple Comparison Procedures

Multiple Comparison Procedures PDF Author: Martin A. Hamilton
Publisher:
ISBN:
Category : Forests and forestry
Languages : en
Pages : 12

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Book Description


Multiple Comparisons

Multiple Comparisons PDF Author: Alan J. Klockars
Publisher: SAGE
ISBN: 9780803920514
Category : Mathematics
Languages : en
Pages : 92

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Book Description
Describes the most important methods used to investigate differences between levels of an independent variable within an experimental design. Readers will learn not only how to conduct multiple comparisons in experimental designs but also how to better understand and evaluate published research. "A highly readable introduction to multiple comparison methods, which demands little from its reader in the way of background other than some familiarity with analysis of variance." --The Statistician

Multiple Comparison Procedures

Multiple Comparison Procedures PDF Author: Yosef Hochberg
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 482

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Book Description
Offering a balanced, up-to-date view of multiple comparison procedures, this book refutes the belief held by some statisticians that such procedures have no place in data analysis. With equal emphasis on theory and applications, it establishes the advantages of multiple comparison techniques in reducing error rates and in ensuring the validity of statistical inferences. Provides detailed descriptions of the derivation and implementation of a variety of procedures, paying particular attention to classical approaches and confidence estimation procedures. Also discusses the benefits and drawbacks of other methods. Numerous examples and tables for implementing procedures are included, making this work both practical and informative.

Dose Finding in Drug Development

Dose Finding in Drug Development PDF Author: Naitee Ting
Publisher: Springer Science & Business Media
ISBN: 0387337067
Category : Medical
Languages : en
Pages : 262

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Book Description
If you have ever wondered when visiting the pharmacy how the dosage of your prescription is determined this book will answer your questions. Dosing information on drug labels is based on discussion between the pharmaceutical manufacturer and the drug regulatory agency, and the label is a summary of results obtained from many scientific experiments. The book introduces the drug development process, the design and the analysis of clinical trials. Many of the discussions are based on applications of statistical methods in the design and analysis of dose response studies. Important procedural steps from a pharmaceutical industry perspective are also examined.

Multiple Testing Problems in Pharmaceutical Statistics

Multiple Testing Problems in Pharmaceutical Statistics PDF Author: Alex Dmitrienko
Publisher: CRC Press
ISBN: 1584889853
Category : Mathematics
Languages : en
Pages : 323

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Book Description
Useful Statistical Approaches for Addressing Multiplicity IssuesIncludes practical examples from recent trials Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple c

Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimation and Hypothesis Testing PDF Author: Rand R. Wilcox
Publisher: Academic Press
ISBN: 0123869838
Category : Mathematics
Languages : en
Pages : 713

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Book Description
"This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"--