Generalized Inference in Repeated Measures - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Generalized Inference in Repeated Measures write by Samaradasa Weerahandi. This book was released on 2004-08-24. Generalized Inference in Repeated Measures available in PDF, EPUB and Kindle. A complete guide to powerful and practical statistical modeling using MANOVA Numerous statistical applications are time dependent. Virtually all biomedical, pharmaceutical, and industrial experiments demand repeated measurements over time. The same holds true for market research and analysis. Yet conventional methods, such as the Repeated Measures Analysis of Variance (Rm ANOVA), do not always yield exact solutions, obliging practitioners to settle for asymptotic results and approximate solutions. Generalized inference in Multivariate Analysis of Variance (MANOVA), mixed models, and growth curves offer exact methods of data analysis under milder conditions without deviating from the conventional philosophy of statistical inference. Generalized Inference in Repeated Measures is a concise, self-contained guide to the use of these innovative solutions, presenting them as extensions of–rather than alternatives to–classical methods of statistical evaluation. Requiring minimal prior knowledge of statistical concepts in the evaluation of linear models, the book provides exact parametric methods for each application considered, with solutions presented in terms of generalized p-values. Coverage includes: New concepts in statistical inference, with special focus on generalized p-values and generalized confidence intervals One-way and two-way ANOVA, in cases of equal and unequal variances Basic and higher-way mixed models, including testing and estimation of fixed effects and variance components Multivariate populations, including basic inference, comparison, and analysis of variance Basic, widely used repeated measures models including crossover designs and growth curves With a comprehensive set of formulas, illustrative examples, and exercises in each chapter, Generalized Inference in Repeated Measures is ideal as both a comprehensive reference for research professionals and a text for students.
Applied Statistics in Agricultural, Biological, and Environmental Sciences
Applied Statistics in Agricultural, Biological, and Environmental Sciences - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applied Statistics in Agricultural, Biological, and Environmental Sciences write by Barry Glaz. This book was released on 2020-01-22. Applied Statistics in Agricultural, Biological, and Environmental Sciences available in PDF, EPUB and Kindle. 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.
Longitudinal Data Analysis
Longitudinal Data Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Longitudinal Data Analysis write by Garrett Fitzmaurice. This book was released on 2008-08-11. Longitudinal Data Analysis available in PDF, EPUB and Kindle. Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory
Exploring Data Tables, Trends, and Shapes
Exploring Data Tables, Trends, and Shapes - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Exploring Data Tables, Trends, and Shapes write by David C. Hoaglin. This book was released on 2011-09-28. Exploring Data Tables, Trends, and Shapes available in PDF, EPUB and Kindle. WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Exploring Data Tables, Trends, and Shapes (EDTTS) was written as a companion volume to the same editors' book, Understanding Robust and Exploratory Data Analysis (UREDA). Whereas UREDA is a collection of exploratory and resistant methods of estimation and display, EDTTS goes a step further, describing multivariate and more complicated techniques . . . I feel that the authors have made a very significant contribution in the area of multivariate nonparametric methods. This book [is] a valuable source of reference to researchers in the area." —Technometrics "This edited volume . . . provides an important theoretical and philosophical extension to the currently popular statistical area of Exploratory Data Analysis, which seeks to reveal structure, or simple descriptions, in data . . . It is . . . an important reference volume which any statistical library should consider seriously." —The Statistician This newly available and affordably priced paperback version of Exploring Data Tables, Trends, and Shapes presents major advances in exploratory data analysis and robust regression methods and explains the techniques, relating them to classical methods. The book addresses the role of exploratory and robust techniques in the overall data-analytic enterprise, and it also presents new methods such as fitting by organized comparisons using the square combining table and identifying extreme cells in a sizable contingency table with probabilistic and exploratory approaches. The book features a chapter on using robust regression in less technical language than available elsewhere. Conceptual support for each technique is also provided.
Computational Molecular Evolution
Computational Molecular Evolution - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Molecular Evolution write by Ziheng Yang. This book was released on 2006-10-05. Computational Molecular Evolution available in PDF, EPUB and Kindle. The field of molecular evolution has experienced explosive growth in recent years due to the rapid accumulation of genetic sequence data, continuous improvements to computer hardware and software, and the development of sophisticated analytical methods. The increasing availability of large genomic data sets requires powerful statistical methods to analyse and interpret them, generating both computational and conceptual challenges for the field. Computational Molecular Evolution provides an up-to-date and comprehensive coverage of modern statistical and computational methods used in molecular evolutionary analysis, such as maximum likelihood and Bayesian statistics. Yang describes the models, methods and algorithms that are most useful for analysing the ever-increasing supply of molecular sequence data, with a view to furthering our understanding of the evolution of genes and genomes. The book emphasizes essential concepts rather than mathematical proofs. It includes detailed derivations and implementation details, as well as numerous illustrations, worked examples, and exercises. It will be of relevance and use to students and professional researchers (both empiricists and theoreticians) in the fields of molecular phylogenetics, evolutionary biology, population genetics, mathematics, statistics and computer science. Biologists who have used phylogenetic software programs to analyze their own data will find the book particularly rewarding, although it should appeal to anyone seeking an authoritative overview of this exciting area of computational biology.
