Regression Analysis and Linear Models

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Publisher : Guilford Publications
ISBN 13 : 1462527981
Total Pages : 689 pages
Book Rating : 4.4/5 (625 download)

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Book Synopsis Regression Analysis and Linear Models by : Richard B. Darlington

Download or read book Regression Analysis and Linear Models written by Richard B. Darlington and published by Guilford Publications. This book was released on 2016-08-22 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing conceptual understanding over mathematics, this user-friendly text introduces linear regression analysis to students and researchers across the social, behavioral, consumer, and health sciences. Coverage includes model construction and estimation, quantification and measurement of multivariate and partial associations, statistical control, group comparisons, moderation analysis, mediation and path analysis, and regression diagnostics, among other important topics. Engaging worked-through examples demonstrate each technique, accompanied by helpful advice and cautions. The use of SPSS, SAS, and STATA is emphasized, with an appendix on regression analysis using R. The companion website (www.afhayes.com) provides datasets for the book's examples as well as the RLM macro for SPSS and SAS. Pedagogical Features: *Chapters include SPSS, SAS, or STATA code pertinent to the analyses described, with each distinctively formatted for easy identification. *An appendix documents the RLM macro, which facilitates computations for estimating and probing interactions, dominance analysis, heteroscedasticity-consistent standard errors, and linear spline regression, among other analyses. *Students are guided to practice what they learn in each chapter using datasets provided online. *Addresses topics not usually covered, such as ways to measure a variable’s importance, coding systems for representing categorical variables, causation, and myths about testing interaction.

Linear Models in Statistics

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Publisher : John Wiley & Sons
ISBN 13 : 0470192607
Total Pages : 690 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Linear Models in Statistics by : Alvin C. Rencher

Download or read book Linear Models in Statistics written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2008-01-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.

Generalized Linear Mixed Models

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Publisher : CRC Press
ISBN 13 : 1439815135
Total Pages : 547 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Generalized Linear Mixed Models by : Walter W. Stroup

Download or read book Generalized Linear Mixed Models written by Walter W. Stroup and published by CRC Press. This book was released on 2016-04-19 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: With numerous examples using SAS PROC GLIMMIX, this text presents an introduction to linear modeling using the generalized linear mixed model as an overarching conceptual framework. For readers new to linear models, the book helps them see the big picture. It shows how linear models fit with the rest of the core statistics curriculum and points out the major issues that statistical modelers must consider.

Hierarchical Linear Modeling

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Publisher : SAGE
ISBN 13 : 1412998859
Total Pages : 393 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis Hierarchical Linear Modeling by : G. David Garson

Download or read book Hierarchical Linear Modeling written by G. David Garson and published by SAGE. This book was released on 2013 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms, followed by a set of original how-to applications articles following a standardard instructional format. The "guide" portion consists of five chapters by the editor, providing an overview of HLM, discussion of methodological assumptions, and parallel worked model examples in SPSS, SAS, and HLM software. The "applications" portion consists of ten contributions in which authors provide step by step presentations of how HLM is implemented and reported for introductory to intermediate applications.

Methods and Applications of Linear Models

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Publisher : John Wiley & Sons
ISBN 13 : 0471458627
Total Pages : 773 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Methods and Applications of Linear Models by : Ronald R. Hocking

Download or read book Methods and Applications of Linear Models written by Ronald R. Hocking and published by John Wiley & Sons. This book was released on 2005-02-04 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: A popular statistical text now updated and better than ever! The ready availability of high-speed computers and statistical software encourages the analysis of ever larger and more complex problems while at the same time increasing the likelihood of improper usage. That is why it is increasingly important to educate end users in the correct interpretation of the methodologies involved. Now in its second edition, Methods and Applications of Linear Models: Regression and the Analysis of Variance seeks to more effectively address the analysis of such models through several important changes. Notable in this new edition: Fully updated and expanded text reflects the most recent developments in the AVE method Rearranged and reorganized discussions of application and theory enhance text’s effectiveness as a teaching tool More than 100 new exercises in the areas of regression and analysis of variance As in the First Edition, the author presents a thorough treatment of the concepts and methods of linear model analysis, and illustrates them with various numerical and conceptual examples, using a data-based approach to development and analysis. Data sets, available on an FTP site, allow readers to apply analytical methods discussed in the book.

Regression & Linear Modeling

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Publisher : SAGE Publications
ISBN 13 : 1506302750
Total Pages : 489 pages
Book Rating : 4.5/5 (63 download)

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Book Synopsis Regression & Linear Modeling by : Jason W. Osborne

Download or read book Regression & Linear Modeling written by Jason W. Osborne and published by SAGE Publications. This book was released on 2016-03-24 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. Author Jason W. Osborne returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.

Hierarchical Linear Models

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Author :
Publisher : SAGE Publications, Incorporated
ISBN 13 :
Total Pages : 294 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Hierarchical Linear Models by : Anthony S. Bryk

Download or read book Hierarchical Linear Models written by Anthony S. Bryk and published by SAGE Publications, Incorporated. This book was released on 1992 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hierarchical Linear Models launches a new Sage series, Advanced Quantitative Techniques in the Social Sciences. This introductory text explicates the theory and use of hierarchical linear models (HLM) through rich, illustrative examples and lucid explanations. The presentation remains reasonably nontechnical by focusing on three general research purposes - improved estimation of effects within an individual unit, estimating and testing hypotheses about cross-level effects, and partitioning of variance and covariance components among levels. This innovative volume describes use of both two and three level models in organizational research, studies of individual development and meta-analysis applications, and concludes with a formal derivation of the statistical methods used in the book.

Advanced Linear Models

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Publisher : Routledge
ISBN 13 : 1351468561
Total Pages : 552 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Advanced Linear Models by : Shein-Chung Chow

Download or read book Advanced Linear Models written by Shein-Chung Chow and published by Routledge. This book was released on 2018-05-04 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work details the statistical inference of linear models including parameter estimation, hypothesis testing, confidence intervals, and prediction. The authors discuss the application of statistical theories and methodologies to various linear models such as the linear regression model, the analysis of variance model, the analysis of covariance model, and the variance components model.

Applied Linear Statistical Models

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Publisher : McGraw-Hill/Irwin
ISBN 13 : 9780072386882
Total Pages : 1396 pages
Book Rating : 4.3/5 (868 download)

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Book Synopsis Applied Linear Statistical Models by : Michael H. Kutner

Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill/Irwin. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Introduction to Linear Models and Statistical Inference

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Publisher : John Wiley & Sons
ISBN 13 : 0471740101
Total Pages : 600 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Introduction to Linear Models and Statistical Inference by : Steven J. Janke

Download or read book Introduction to Linear Models and Statistical Inference written by Steven J. Janke and published by John Wiley & Sons. This book was released on 2005-09-15 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: A multidisciplinary approach that emphasizes learning by analyzing real-world data sets This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. These examples are developed and analyzed throughout the text, and more complicated examples of data sets are introduced along the way. Taking a multidisciplinary approach, the book traces the conclusion of the analyses of data sets taken from geology, biology, economics, psychology, education, sociology, and environmental science. As students learn to analyze the data sets, they master increasingly sophisticated linear modeling techniques, including: * Simple linear models * Multivariate models * Model building * Analysis of variance (ANOVA) * Analysis of covariance (ANCOVA) * Logistic regression * Total least squares The basics of statistical analysis are developed and emphasized, particularly in testing the assumptions and drawing inferences from linear models. Exercises are included at the end of each chapter to test students' skills before moving on to more advanced techniques and models. These exercises are marked to indicate whether calculus, linear algebra, or computer skills are needed. Unlike other texts in the field, the mathematics underlying the models is carefully explained and accessible to students who may not have any background in calculus or linear algebra. Most chapters include an optional final section on linear algebra for students interested in developing a deeper understanding. The many data sets that appear in the text are available on the book's Web site. The MINITAB(r) software program is used to illustrate many of the examples. For students unfamiliar with MINITAB(r), an appendix introduces the key features needed to study linear models. With its multidisciplinary approach and use of real-world data sets that bring the subject alive, this is an excellent introduction to linear models for students in any of the natural or social sciences.

Regression Modeling Strategies

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Publisher : Springer Science & Business Media
ISBN 13 : 147573462X
Total Pages : 583 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Regression Modeling Strategies by : Frank E. Harrell

Download or read book Regression Modeling Strategies written by Frank E. Harrell and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".

Linear Models with R

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Publisher : CRC Press
ISBN 13 : 1439887349
Total Pages : 284 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Linear Models with R by : Julian J. Faraway

Download or read book Linear Models with R written by Julian J. Faraway and published by CRC Press. This book was released on 2016-04-19 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Hands-On Way to Learning Data AnalysisPart of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models

Methods and Applications of Longitudinal Data Analysis

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Publisher : Elsevier
ISBN 13 : 0128014822
Total Pages : 531 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Methods and Applications of Longitudinal Data Analysis by : Xian Liu

Download or read book Methods and Applications of Longitudinal Data Analysis written by Xian Liu and published by Elsevier. This book was released on 2015-09-01 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical applications across many areas of research. Statistical procedures featured within the text include: - descriptive methods for delineating trends over time - linear mixed regression models with both fixed and random effects - covariance pattern models on correlated errors - generalized estimating equations - nonlinear regression models for categorical repeated measurements - techniques for analyzing longitudinal data with non-ignorable missing observations Emphasis is given to applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data. Methods and Applications of Longitudinal Data Analysis equips both graduate students and professionals to confidently apply longitudinal data analysis to their particular discipline. It also provides a valuable reference source for applied statisticians, demographers and other quantitative methodologists. - From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis - Enables students to select the correct statistical methods to apply to their longitudinal data and avoid the pitfalls associated with incorrect selection - Identifies the limitations of classical repeated measures models and describes newly developed techniques, along with real-world examples.

Linear Models

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Publisher : John Wiley & Sons
ISBN 13 : 9780470377970
Total Pages : 288 pages
Book Rating : 4.3/5 (779 download)

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Book Synopsis Linear Models by : Brenton R. Clarke

Download or read book Linear Models written by Brenton R. Clarke and published by John Wiley & Sons. This book was released on 2008-09-19 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: An insightful approach to the analysis of variance in the study of linear models Linear Models explores the theory of linear models and the dynamic relationships that these models have with Analysis of Variance (ANOVA), experimental design, and random and mixed-model effects. This one-of-a-kind book emphasizes an approach that clearly explains the distribution theory of linear models and experimental design starting from basic mathematical concepts in linear algebra. The author begins with a presentation of the classic fixed-effects linear model and goes on to illustrate eight common linear models, along with the value of their use in statistics. From this foundation, subsequent chapters introduce concepts pertaining to the linear model, starting with vector space theory and the theory of least-squares estimation. An outline of the Helmert matrix is also presented, along with a thorough explanation of how the ANOVA is created in both typical two-way and higher layout designs, ultimately revealing the distribution theory. Other important topics covered include: Vector space theory The theory of least squares estimation Gauss-Markov theorem Kronecker products Diagnostic and robust methods for linear models Likelihood approaches to estimation A discussion of Bayesian theory is also included for purposes of comparison and contrast, and numerous illustrative exercises assist the reader with uncovering the nature of the models, using both classic and new data sets. Requiring only a working knowledge of basic probability and statistical inference, Linear Models is a valuable book for courses on linear models at the upper-undergraduate and graduate levels. It is also an excellent reference for practitioners who use linear models to conduct research in the fields of econometrics, psychology, sociology, biology, and agriculture.

Theory and Application of the Linear Model

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Author :
Publisher : Brooks/Cole
ISBN 13 :
Total Pages : 724 pages
Book Rating : 4.:/5 (321 download)

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Book Synopsis Theory and Application of the Linear Model by : Franklin A. Graybill

Download or read book Theory and Application of the Linear Model written by Franklin A. Graybill and published by Brooks/Cole. This book was released on 2000 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: In THEORY AND APPLICATION OF THE LINEAR MODEL, Franklin A. Graybill integrates the linear statistical model within the context of analysis of variance, correlation and regression, and design of experiments. With topics motivated by real situations, it is a time tested, authoritative resource for experimenters, statistical consultants, and students.

Interaction Effects in Linear and Generalized Linear Models

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Publisher : SAGE Publications
ISBN 13 : 1506365361
Total Pages : 427 pages
Book Rating : 4.5/5 (63 download)

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Book Synopsis Interaction Effects in Linear and Generalized Linear Models by : Robert L. Kaufman

Download or read book Interaction Effects in Linear and Generalized Linear Models written by Robert L. Kaufman and published by SAGE Publications. This book was released on 2018-09-06 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is remarkable in its accessible treatment of interaction effects. Although this concept can be challenging for students (even those with some background in statistics), this book presents the material in a very accessible manner, with plenty of examples to help the reader understand how to interpret their results." –Nicole Kalaf-Hughes, Bowling Green State University Offering a clear set of workable examples with data and explanations, Interaction Effects in Linear and Generalized Linear Models is a comprehensive and accessible text that provides a unified approach to interpreting interaction effects. The book develops the statistical basis for the general principles of interpretive tools and applies them to a variety of examples, introduces the ICALC Toolkit for Stata, and offers a series of start-to-finish application examples to show students how to interpret interaction effects for a variety of different techniques of analysis, beginning with OLS regression. The author’s website provides a downloadable toolkit of Stata® routines to produce the calculations, tables, and graphics for each interpretive tool discussed. Also available are the Stata® dataset files to run the examples in the book.

Linear Models and Generalizations

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Publisher : Springer Science & Business Media
ISBN 13 : 3540742271
Total Pages : 583 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Linear Models and Generalizations by : C. Radhakrishna Rao

Download or read book Linear Models and Generalizations written by C. Radhakrishna Rao and published by Springer Science & Business Media. This book was released on 2007-10-15 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: Revised and updated with the latest results, this Third Edition explores the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions. They not only use least squares theory, but also alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights of coverage include sensitivity analysis and model selection, an analysis of incomplete data, an analysis of categorical data based on a unified presentation of generalized linear models, and an extensive appendix on matrix theory.