› › A Comparison Of Five Robust Regression Methods With Ordinary Least Squares

Robust Estimation and Testing

Author : Robert G. Staudte

Publisher : John Wiley & Sons

Page : 382 pages

File Size : 33,5 MB

Release : 2011-09-15

Category : Mathematics

ISBN : 1118165497

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Book Description

An introduction to the theory and methods of robust statistics, providing students with practical methods for carrying out robust procedures in a variety of statistical contexts and explaining the advantages of these procedures. In addition, the text develops techniques and concepts likely to be useful in the future analysis of new statistical models and procedures. Emphasizing the concepts of breakdown point and influence functon of an estimator, it demonstrates the technique of expressing an estimator as a descriptive measure from which its influence function can be derived and then used to explore the efficiency and robustness properties of the estimator. Mathematical techniques are complemented by computational algorithms and Minitab macros for finding bootstrap and influence function estimates of standard errors of the estimators, robust confidence intervals, robust regression estimates and their standard errors. Includes examples and problems.



A Beginner's Guide to Structural Equation Modeling

Author : Randall E. Schumacker

Publisher : Routledge

Page : 532 pages

File Size : 39,25 MB

Release : 2012-10-12

Category : Psychology

ISBN : 1136968555

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Book Description

This best-seller introduces readers to structural equation modeling (SEM) so they can conduct their own analysis and critique related research. Noted for its accessible, applied approach, chapters cover basic concepts and practices and computer input/output from the free student version of Lisrel 8.8 in the examples. Each chapter features an outline, key concepts, a summary, numerous examples from a variety of disciplines, tables, and figures, including path diagrams, to assist with conceptual understanding. The book first reviews the basics of SEM, data entry/editing, and correlation. Next the authors highlight the basic steps of SEM: model specification, identification, estimation, testing, and modification, followed by issues related to model fit and power and sample size. Chapters 6 through 10 follow the steps of modeling using regression, path, confirmatory factor, and structural equation models. Next readers find a chapter on reporting SEM research including a checklist to guide decision-making, followed by one on model validation. Chapters 13 through 16 provide examples of various SEM model applications. The book concludes with the matrix approach to SEM using examples from previous chapters. Highlights of the new edition include: A website with raw data sets for the book's examples and exercises so they can be used with any SEM program, all of the book's exercises, hotlinks to related websites, and answers to all of the exercises for Instructor’s only New troubleshooting tips on how to address the most frequently encountered problems Examples now reference the free student version of Lisrel 8.8 Expanded coverage of advanced models with more on multiple-group, multi-level, & mixture modeling (Chs. 13 & 15), second-order and dynamic factor models (Ch. 14), and Monte Carlo methods (Ch. 16) Increased coverage of sample size and power (Ch. 5) and reporting research (Ch. 11) New journal article references help readers better understand published research (Chs. 13 – 17) and 25 % new exercises with answers to half in the book for student review. Designed for introductory graduate level courses in structural equation modeling or factor analysis taught in psychology, education, business, and the social and healthcare sciences, this practical book also appeals to researchers in these disciplines. An understanding of correlation is assumed. To access the website visit the book page or the Textbook Resource page at http://www.psypress.com/textbook-resources/ for more details.



Serious Stat

Author : Thomas Baguley

Publisher : Bloomsbury Publishing

Page : 864 pages

File Size : 20,10 MB

Release : 2018-01-24

Category : Psychology

ISBN : 0230363555

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Book Description

Ideal for experienced students and researchers in the social sciences who wish to refresh or extend their understanding of statistics, and to apply advanced statistical procedures using SPSS or R. Key theory is reviewed and illustrated with examples of how to apply these concepts using real data.



A Beginner's Guide to Structural Equation Modeling

Author : Tiffany A. Whittaker

Publisher : Routledge

Page : 419 pages

File Size : 30,65 MB

Release : 2022-04-27

Category : Psychology

ISBN : 1000569748

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Book Description

A Beginner’s Guide to Structural Equation Modeling, fifth edition, has been redesigned with consideration of a true beginner in structural equation modeling (SEM) in mind. The book covers introductory through intermediate topics in SEM in more detail than in any previous edition. All of the chapters that introduce models in SEM have been expanded to include easy-to-follow, step-by-step guidelines that readers can use when conducting their own SEM analyses. These chapters also include examples of tables to include in results sections that readers may use as templates when writing up the findings from their SEM analyses. The models that are illustrated in the text will allow SEM beginners to conduct, interpret, and write up analyses for observed variable path models to full structural models, up to testing higher order models as well as multiple group modeling techniques. Updated information about methodological research in relevant areas will help students and researchers be more informed readers of SEM research. The checklist of SEM considerations when conducting and reporting SEM analyses is a collective set of requirements that will help improve the rigor of SEM analyses. This book is intended for true beginners in SEM and is designed for introductory graduate courses in SEM taught in psychology, education, business, and the social and healthcare sciences. This book also appeals to researchers and faculty in various disciplines. Prerequisites include correlation and regression methods.



RTI Approach to Evaluating Learning Disabilities

Author : Joseph F. Kovaleski

Publisher : Guilford Publications

Page : 290 pages

File Size : 18,29 MB

Release : 2022-11-11

Category : Education

ISBN : 1462550444

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Book Description

From leading authorities, this indispensable work is now in a revised and expanded second edition, presenting state-of-the-art tools and procedures for practitioners. The book shows how to use response to intervention (RTI) to evaluate K–12 students for specific learning disabilities (SLD). The second edition gives increased attention to optimizing the instructional environment in the context of a multi-tiered system of supports (MTSS). Procedures are described for screening at-risk students; using RTI to intensify instruction in reading, writing, and math; identifying SLD; determining eligibility for special education; and planning individualized education programs. Case examples and pointers for practice are woven throughout. In a convenient large-size format, the book includes reproducible tools that can be downloaded and printed for repeated use. New to This Edition *Incorporates contemporary perspectives on SLD, upgraded procedures for implementing an MTSS, new approaches to measuring RTI, and enhancements in using classroom observations. *Chapter on best practices in academic screening, including important dos and don'ts. *Separate chapters on using RTI for reading, written expression, and mathematics. *Chapter on RTI and special education law, focusing on what practitioners need to know. This book is in The Guilford Practical Intervention in the Schools Series, edited by Sandra M. Chafouleas.



Robust Statistical Procedures

Author : Peter J. Huber

Publisher : SIAM

Page : 77 pages

File Size : 38,35 MB

Release : 1996-01-01

Category : Mathematics

ISBN : 9781611970036

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Book Description

Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in robustness has been added and the reference list has been expanded and updated from the 1977 edition.



Spatial Analysis Methods and Practice

Author : George Grekousis

Publisher : Cambridge University Press

Page : 535 pages

File Size : 48,2 MB

Release : 2020-06-11

Category : Reference

ISBN : 1108498981

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Book Description

An introductory overview of spatial analysis and statistics through GIS, including worked examples and critical analysis of results.



Alternative Methods of Regression

Author : David Birkes

Publisher : John Wiley & Sons

Page : 248 pages

File Size : 31,17 MB

Release : 2011-09-20

Category : Mathematics

ISBN : 1118150244

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Book Description

Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data sets real. Topics include: multi-response parameter estimation; models defined by systems of differential equations; and improved methods for presenting inferential results of nonlinear analysis. 1988 (0-471-81643-4) 365 pp. Nonlinear Regression G. A. F. Seber and C. J. Wild ".[a] comprehensive and scholarly work.impressively thorough with attention given to every aspect of the modeling process." --Short Book Reviews of the International Statistical Institute In this introduction to nonlinear modeling, the authors examine a wide range of estimation techniques including least squares, quasi-likelihood, and Bayesian methods, and discuss some of the problems associated with estimation. The book presents new and important material relating to the concept of curvature and its growing role in statistical inference. It also covers three useful classes of models --growth, compartmental, and multiphase --and emphasizes the limitations involved in fitting these models. Packed with examples and graphs, it offers statisticians, statistical consultants, and statistically oriented research scientists up-to-date access to their fields. 1989 (0-471-61760-1) 768 pp. Mathematical Programming in Statistics T. S. Arthanari and Yadolah Dodge "The authors have achieved their stated intention.in an outstanding and useful manner for both students and researchers.Contains a superb synthesis of references linked to the special topics and formulations by a succinct set of bibliographical notes.Should be in the hands of all system analysts and computer system architects." --Computing Reviews This unique book brings together most of the available results on applications of mathematical programming in statistics, and also develops the necessary statistical and programming theory and methods. 1981 (0-471-08073-X) 413 pp.



Robust Regression and Outlier Detection

Author : Peter J. Rousseeuw

Publisher : John Wiley & Sons

Page : 329 pages

File Size : 50,54 MB

Release : 2005-02-25

Category : Mathematics

ISBN : 0471725374

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Book Description

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selectedbooks that have been made more accessible to consumers in an effortto increase global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "The writing style is clear and informal, and much of thediscussion is oriented to application. In short, the book is akeeper." –Mathematical Geology "I would highly recommend the addition of this book to thelibraries of both students and professionals. It is a usefultextbook for the graduate student, because it emphasizes both thephilosophy and practice of robustness in regression settings, andit provides excellent examples of precise, logical proofs oftheorems. . . .Even for those who are familiar with robustness, thebook will be a good reference because it consolidates the researchin high-breakdown affine equivariant estimators and includes anextensive bibliography in robust regression, outlier diagnostics,and related methods. The aim of this book, the authors tell us, is‘to make robust regression available for everyday statisticalpractice.’ Rousseeuw and Leroy have included all of thenecessary ingredients to make this happen." –Journal of the American Statistical Association



Applied Linear Statistical Models

Author : Michael H. Kutner

Publisher : McGraw-Hill/Irwin

Page : 1396 pages

File Size : 15,76 MB

Release : 2005

Category : Mathematics

ISBN : 9780072386882

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Book Description

Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.