Analysis Of Variance And Covariance
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Author |
: C. Patrick Doncaster |
Publisher |
: Cambridge University Press |
Total Pages |
: 304 |
Release |
: 2007-08-30 |
ISBN-10 |
: 052186562X |
ISBN-13 |
: 9780521865623 |
Rating |
: 4/5 (2X Downloads) |
Synopsis Analysis of Variance and Covariance by : C. Patrick Doncaster
Analysis of variance (ANOVA) is a core technique for analysing data in the Life Sciences. This reference book bridges the gap between statistical theory and practical data analysis by presenting a comprehensive set of tables for all standard models of analysis of variance and covariance with up to three treatment factors. The book will serve as a tool to help post-graduates and professionals define their hypotheses, design appropriate experiments, translate them into a statistical model, validate the output from statistics packages and verify results. The systematic layout makes it easy for readers to identify which types of model best fit the themes they are investigating, and to evaluate the strengths and weaknesses of alternative experimental designs. In addition, a concise introduction to the principles of analysis of variance and covariance is provided, alongside worked examples illustrating issues and decisions faced by analysts.
Author |
: Bradley Huitema |
Publisher |
: John Wiley & Sons |
Total Pages |
: 562 |
Release |
: 2011-10-24 |
ISBN-10 |
: 9781118067468 |
ISBN-13 |
: 1118067460 |
Rating |
: 4/5 (68 Downloads) |
Synopsis The Analysis of Covariance and Alternatives by : Bradley Huitema
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.
Author |
: Alan C. Elliott |
Publisher |
: SAGE |
Total Pages |
: 280 |
Release |
: 2007 |
ISBN-10 |
: 1412925606 |
ISBN-13 |
: 9781412925600 |
Rating |
: 4/5 (06 Downloads) |
Synopsis Statistical Analysis Quick Reference Guidebook by : Alan C. Elliott
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.
Author |
: Albert R. Wildt |
Publisher |
: SAGE |
Total Pages |
: 100 |
Release |
: 1978-11 |
ISBN-10 |
: 0803911645 |
ISBN-13 |
: 9780803911642 |
Rating |
: 4/5 (45 Downloads) |
Synopsis Analysis of Covariance by : Albert R. Wildt
This book presents a technique for analyzing the effects of variables, groups, and treatments in both experimental and observational settings. It considers not only the main effects of one variable upon another, but also the effects of group cases.
Author |
: Howard E.A. Tinsley |
Publisher |
: Academic Press |
Total Pages |
: 751 |
Release |
: 2000-05-22 |
ISBN-10 |
: 9780080533568 |
ISBN-13 |
: 0080533566 |
Rating |
: 4/5 (68 Downloads) |
Synopsis Handbook of Applied Multivariate Statistics and Mathematical Modeling by : Howard E.A. Tinsley
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.
Author |
: Jin-Ting Zhang |
Publisher |
: CRC Press |
Total Pages |
: 406 |
Release |
: 2013-06-18 |
ISBN-10 |
: 9781439862742 |
ISBN-13 |
: 1439862745 |
Rating |
: 4/5 (42 Downloads) |
Synopsis Analysis of Variance for Functional Data by : Jin-Ting Zhang
Despite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date hypothesis testing methods for functional data analysis. The book covers the reconstruction of functional observations, functional ANOVA, functional l
Author |
: Ronald Christensen |
Publisher |
: CRC Press |
Total Pages |
: 608 |
Release |
: 1996-06-01 |
ISBN-10 |
: 0412062917 |
ISBN-13 |
: 9780412062919 |
Rating |
: 4/5 (17 Downloads) |
Synopsis Analysis of Variance, Design, and Regression by : Ronald Christensen
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.
Author |
: Robert K. Leik |
Publisher |
: SAGE Publications |
Total Pages |
: 209 |
Release |
: 1997-04-19 |
ISBN-10 |
: 9781452250359 |
ISBN-13 |
: 1452250359 |
Rating |
: 4/5 (59 Downloads) |
Synopsis Experimental Design and the Analysis of Variance by : Robert K. Leik
Why is this Book a Useful Supplement for Your Statistics Course? Most core statistics texts cover subjects like analysis of variance and regression, but not in much detail. This book, as part of our Series in Research Methods and Statistics, provides you with the flexibility to cover ANOVA more thoroughly, but without financially overburdening your students.
Author |
: Elliot T. Berkman |
Publisher |
: SAGE |
Total Pages |
: 313 |
Release |
: 2012 |
ISBN-10 |
: 9781412974066 |
ISBN-13 |
: 1412974062 |
Rating |
: 4/5 (66 Downloads) |
Synopsis A Conceptual Guide to Statistics Using SPSS by : Elliot T. Berkman
This book helps students develop a conceptual understanding of a variety of statistical tests by linking the statistics with the computational steps and output from SPSS. Learning how statistical ideas map onto computation in SPSS will help students build a better understanding of both. For example, seeing exactly how the concept of variance is used in SPSS-how it is converted into a number based on real data, which other concepts it is associated with, and where it appears in various statistical tests-will not only help students understand how to use statistical tests in SPSS and how to interpret their output, but will also teach them about the concept of variance itself. Each chapter begins with a student-friendly explanation of the concept behind each statistical test and how the test relates to that concept. The authors then walk through the steps to compute the test in SPSS and the output, pointing out wherever possible how the SPSS procedure and output connects back to the conceptual underpinnings of the test. Each of the steps is accompanied by annotated screen shots from SPSS, and relevant components of output are highlighted in both the text and in the figures. Sections explain the conceptual machinery underlying the statistical tests. In contrast to merely presenting the equations for computing the statistic, these sections describe the idea behind each test in plain language and help students make the connection between the ideas and SPSS procedures. These include extensive treatment of custom hypothesis testing in ANOVA, MANOVA, ANCOVA, and regression, and an entire chapter on the advanced matrix algebra functions available only through syntax in SPSS. The book will be appropriate for both advanced undergraduate and graduate level courses in statistics.
Author |
: Henry Scheffé |
Publisher |
: John Wiley & Sons |
Total Pages |
: 500 |
Release |
: 1999-03-05 |
ISBN-10 |
: 0471345059 |
ISBN-13 |
: 9780471345053 |
Rating |
: 4/5 (59 Downloads) |
Synopsis The Analysis of Variance by : Henry Scheffé
Originally published in 1959, this classic volume has had a major impact on generations of statisticians. Newly issued in the Wiley Classics Series, the book examines the basic theory of analysis of variance by considering several different mathematical models. Part I looks at the theory of fixed-effects models with independent observations of equal variance, while Part II begins to explore the analysis of variance in the case of other models.