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Analysis Of Variance And Covariance


Analysis Of Variance And Covariance
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Statistical Analysis Quick Reference Guidebook


Statistical Analysis Quick Reference Guidebook
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Author : Alan C. Elliott
language : en
Publisher: SAGE
Release Date : 2007

Statistical Analysis Quick Reference Guidebook written by Alan C. Elliott and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.


A practical `cut to the chase′ handbook that quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision-making in a wide variety of disciplines. In this one-stop reference, the authors provide succinct guidelines for performing an analysis, avoiding pitfalls, interpreting results and reporting outcomes.



The Analysis Of Covariance And Alternatives


The Analysis Of Covariance And Alternatives
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Author : Bradley Huitema
language : en
Publisher: John Wiley & Sons
Release Date : 2011-10-24

The Analysis Of Covariance And Alternatives written by Bradley Huitema and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-24 with Mathematics categories.


A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.



Handbook Of Applied Multivariate Statistics And Mathematical Modeling


Handbook Of Applied Multivariate Statistics And Mathematical Modeling
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Author : Howard E.A. Tinsley
language : en
Publisher: Academic Press
Release Date : 2000-05-22

Handbook Of Applied Multivariate Statistics And Mathematical Modeling written by Howard E.A. Tinsley and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-22 with Mathematics categories.


Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.



Analysis Of Covariance


Analysis Of Covariance
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Author : Albert R. Wildt
language : en
Publisher: SAGE
Release Date : 1978-11

Analysis Of Covariance written by Albert R. Wildt and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978-11 with Mathematics categories.


This series of methodological works provides introductory explanations and demonstration of various data analysis techniques applicable to the social sciences. Designed for readers with a limited background in statistics or mathematics, this series aims to make the assumptions and practices of quantitative analysis more readily accessible.



Anova And Ancova


Anova And Ancova
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Author : Andrew Rutherford
language : en
Publisher: John Wiley & Sons
Release Date : 2011-10-25

Anova And Ancova written by Andrew Rutherford and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-25 with Mathematics categories.


Provides an in-depth treatment of ANOVA and ANCOVA techniques from a linear model perspective ANOVA and ANCOVA: A GLM Approach provides a contemporary look at the general linear model (GLM) approach to the analysis of variance (ANOVA) of one- and two-factor psychological experiments. With its organized and comprehensive presentation, the book successfully guides readers through conventional statistical concepts and how to interpret them in GLM terms, treating the main single- and multi-factor designs as they relate to ANOVA and ANCOVA. The book begins with a brief history of the separate development of ANOVA and regression analyses, and then goes on to demonstrate how both analyses are incorporated into the understanding of GLMs. This new edition now explains specific and multiple comparisons of experimental conditions before and after the Omnibus ANOVA, and describes the estimation of effect sizes and power analyses leading to the determination of appropriate sample sizes for experiments to be conducted. Topics that have been expanded upon and added include: Discussion of optimal experimental designs Different approaches to carrying out the simple effect analyses and pairwise comparisons with a focus on related and repeated measure analyses The issue of inflated Type 1 error due to multiple hypotheses testing Worked examples of Shaffer's R test, which accommodates logical relations amongst hypotheses ANOVA and ANCOVA: A GLM Approach, Second Edition is an excellent book for courses on linear modeling at the graduate level. It is also a suitable reference for researchers and practitioners in the fields of psychology and the biomedical and social sciences.



Analysis Of Variance For Functional Data


Analysis Of Variance For Functional Data
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Author : Jin-Ting Zhang
language : en
Publisher:
Release Date : 2024-10-14

Analysis Of Variance For Functional Data written by Jin-Ting Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-14 with Mathematics categories.


This self-contained book presents up-to-date hypothesis testing methods for functional data analysis. Useful for statistical researchers and practitioners analyzing functional data, it gives both a theoretical and applied treatment of functional data analysis supported by easy-to-use MATLAB(R) code. The book covers the reconstruction of



Analysis Of Variance Design And Regression


Analysis Of Variance Design And Regression
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Author : Ronald Christensen
language : en
Publisher: CRC Press
Release Date : 1996-06-01

Analysis Of Variance Design And Regression written by Ronald Christensen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-06-01 with Mathematics categories.


This text presents a comprehensive treatment of basic statistical methods and their applications. It focuses on the analysis of variance and regression, but also addressing basic ideas in experimental design and count data. The book has four connecting themes: similarity of inferential procedures, balanced one-way analysis of variance, comparison of models, and checking assumptions. Most inferential procedures are based on identifying a scalar parameter of interest, estimating that parameter, obtaining the standard error of the estimate, and identifying the appropriate reference distribution. Given these items, the inferential procedures are identical for various parameters. Balanced one-way analysis of variance has a simple, intuitive interpretation in terms of comparing the sample variance of the group means with the mean of the sample variance for each group. All balanced analysis of variance problems are considered in terms of computing sample variances for various group means. Comparing different models provides a structure for examining both balanced and unbalanced analysis of variance problems and regression problems. Checking assumptions is presented as a crucial part of every statistical analysis. Examples using real data from a wide variety of fields are used to motivate theory. Christensen consistently examines residual plots and presents alternative analyses using different transformation and case deletions. Detailed examination of interactions, three factor analysis of variance, and a split-plot design with four factors are included. The numerous exercises emphasize analysis of real data. Senior undergraduate and graduate students in statistics and graduate students in other disciplines using analysis of variance, design of experiments, or regression analysis will find this book useful.



Making Sense Of Multivariate Data Analysis


Making Sense Of Multivariate Data Analysis
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Author : John Spicer
language : en
Publisher: SAGE
Release Date : 2005

Making Sense Of Multivariate Data Analysis written by John Spicer and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Mathematics categories.


A short introduction to the subject, this text is aimed at students & practitioners in the behavioural & social sciences. It offers a conceptual overview of the foundations of MDA & of a range of specific techniques including multiple regression, logistic regression & log-linear analysis.



Introducing Anova And Ancova


Introducing Anova And Ancova
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Author : Andrew Rutherford
language : en
Publisher: SAGE
Release Date : 2001-03-08

Introducing Anova And Ancova written by Andrew Rutherford and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-03-08 with Social Science categories.


Traditional approaches to ANOVA and ANCOVA are now being replaced by a General Linear Modeling (GLM) approach. This book begins with a brief history of the separate development of ANOVA and regression analyses and demonstrates how both analysis forms are subsumed by the General Linear Model. A simple single independent factor ANOVA is analysed first in conventional terms and then again in GLM terms to illustrate the two approaches. The text then goes on to cover the main designs, both independent and related ANOVA and ANCOVA, single and multi-factor designs. The conventional statistical assumptions underlying ANOVA and ANCOVA are detailed and given expression in GLM terms. Alternatives to traditional ANCO



Variance Components


Variance Components
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Author : Shayle R. Searle
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-25

Variance Components written by Shayle R. Searle and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-25 with Mathematics categories.


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. ". . .Variance Components is an excellent book. It is organized and well written, and provides many references to a variety of topics. I recommend it to anyone with interest in linear models." —Journal of the American Statistical Association "This book provides a broad coverage of methods for estimating variance components which appeal to students and research workers . . . The authors make an outstanding contribution to teaching and research in the field of variance component estimation." —Mathematical Reviews "The authors have done an excellent job in collecting materials on a broad range of topics. Readers will indeed gain from using this book . . . I must say that the authors have done a commendable job in their scholarly presentation." —Technometrics This book focuses on summarizing the variability of statistical data known as the analysis of variance table. Penned in a readable style, it provides an up-to-date treatment of research in the area. The book begins with the history of analysis of variance and continues with discussions of balanced data, analysis of variance for unbalanced data, predictions of random variables, hierarchical models and Bayesian estimation, binary and discrete data, and the dispersion mean model.