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Statistics for Engineers and Scientists
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William C Navidi
Real World Data Sets with new problems along with ARIS, McGraw-Hill's "Homework Management System", define what this second edition has to offer. Within ARIS, Navidi offers 300 algorithmic practice problems along with Java applets that allow students to interactively explore ideas in the text. Customizable PowerPoint lecture notes for each chapter ...
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Hierarchical Linear Models: Applications and Data Analysis Methods
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Dr. Stephen W Raudenbush, Dr. Anthony S Bryk
Popular in its first edition for its rich, illustrative examples and lucid explanations of the theory and use of hierarchical linear models (HLM), the book has been updated to include: an intuitive introductory summary of the basic procedures for estimation and inference used with HLM models that only requires a minimal level of mathematical ...
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Applied Linear Statistical Models: Regression, Analysis of Variance, and Experimental Designs
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by
John Neter
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Generalized, linear, and mixed models
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by
Charles E McCulloch, Shayle Robert Searle
This book provides an accessible and self-contained introduction to statistical models - now in a modernized new edition. "Generalized, Linear, and Mixed Models, Second Edition" provides an up-to-date treatment of the essential techniques for developing and applying a wide variety of statistical models. The book presents thorough and unified ...
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Plane Answers to Complex Questions: The Theory of Linear Models
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Ronald Christensen
This textbook provides a wide-ranging introduction to the use and theory of linear models for analyzing data. The author's emphasis is on providing a unified treatment of linear models, including analysis of variance models and regression models, based on projections, orthogonality, and other vector space ideas. Every chapter comes with numerous ...
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Fixed Effects Regression Methods for Longitudinal Data Using SAS
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Paul D Allison
An invaluable resource, this straightforward and thorough text reveals how to estimate fixed effects models with several SAS procedures that are appropriate for different kinds of outcome variables. This book is designed for all researchers interested in adding fixed effects regression methods to their tool kit of statistical techniques.
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Linear Models
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by
Shayle Robert Searle
This 1971 classic on linear models is once again available--as a Wiley Classics Library Edition. It features material that can be understood by any statistician who understands matrix algebra and basic statistical methods.
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The Theory of Linear Economic Models
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by
David Gale
In the past few decades, methods of linear algebra have become central to economic analysis, replacing older tools such as the calculus. David Gale has provided the first complete and lucid treatment of important topics in mathematical economics which can be analyzed by linear models. This self-contained work requires few mathematical ...
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Linear Models for Unbalanced Data
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by
Shayle Robert Searle
"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, ...
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Linear Models in Statistics
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by
Alvin C Rencher
This is 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 necessary 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 ...
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Applied Regression Analysis, Linear Models, and Related Methods
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by
John Fox
An accessible, detailed and up-to-date treatment of regression analysis, linear models and closely related methods is provided in this book. Incorporating nearly 200 graphs and numerous examples and exercises that employ real data from the social sciences, the book begins with a consideration of the role of statistical data analysis in social ...
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Generalized Linear Models for Insurance Data
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by
Piet De Jong, Gillian Z Heller
This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book ...
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An Introduction to Generalized Linear Models
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by
Annette J Dobson, Adrian G Barnett
Popular for its accessible, concise, and clear introduction to this key statistical methodology, "An Introduction to Generalized Linear Models, Third Edition" provides a wealth of examples from such diverse fields as business, medicine, engineering, and the social sciences. Emphasizing graphical methods for exploratory data analysis and ...
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Generalized Additive Models: An Introduction with R
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Simon N Wood
Now in widespread use, generalized additive models (GAMs) have evolved into a standard statistical methodology of considerable flexibility. While Hastie and Tibshirani's outstanding 1990 research monograph on GAMs is largely responsible for this, there has been a long-standing need for an accessible introductory treatment of the subject that also ...
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Applied Linear Statistical Models
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by
Michael H Kutner, PH.D., Chris J Nachtsheim, PH.D., William Li
This new edition of "Applied Linear Statistical Models "retains the book's uniquely straightforward writing style and format while providing you with the latest information and knowledge. Updates include developments and methods in partial regression and residual plots, an entirely new introduction to the "Design of Experiments" section that ...
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Applied Linear Statistical Models
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by
John Neter, Michael H Kutner, PH.D., William Wasserman
This text uses an applied approach, with an emphasis on the understanding of concepts and exposition by means of examples. Sufficient theoretical information is provided to enable applications of regression analysis to be carried out. Case studies are used to illustrate many of the statistical methods. There is coverage of composite designs for ...
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First Course in Linear Model Theory
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by
Nalini Ravishanker, Dipak K Dey
This innovative, intermediate-level statistics text fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an innovative approach, the authors' introduce students to the mathematical and statistical concepts and tools that form a foundation ...
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Matrix Algebra from a Statistician's Perspective
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by
David A Harville
This book presents matrix algebra in a way that is well-suited for those with an interest in statistics or a related discipline. It provides thorough and unified coverage of the fundamental concepts along with the specialized topics encountered in areas of statistics such as linear statistical models and multivariate analysis. It includes a number ...
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Generalized Linear Models
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by
John P Hoffmann
This brief and economical text shows students with relatively little mathematical background how to understand and apply sophisticated linear regression models in their research areas within the social, behavioral, and medical sciences, as well as marketing, and business. Less theoretical than competing texts, Hoffman includes numerous exercises ...
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Linear Models for Optimal Test Design
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by
Wim J Van Der Linden, W J Van Der Linden
This book begins with a reflection on the history of test design - the core activity of all educational and psychological testing. It then presents a standard language for modeling test design problems as instances of multi-objective constrained optimization. The main portion of the book discusses test design models for a large variety of problems ...
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Parameter Estimation and Hypothesis Testing in Linear Models
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by
Karl-Rudolf Koch
This textbook deals with the estimation of unknown parameters, the testing of hypotheses and the estimation of confidence intervals in linear models. The reader will find presentations of the Gauss-Markoff model, the analysis of variance, the multivariate model, the model with unknown variance and covariance components and the regression model as ...
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Regression Analysis: Statistical Modeling of a Response Variable
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by
Rudolf Jakob Freund (Editor), William J Wilson (Editor)
Regression Analysis provides students with the skills and techniques necessary for the intelligent statistical analysis of a response variable. The book underscores statistical concepts, de-emphasizes formulas, and incorporates real data from the most popular package at this level, SAS. Regression Analysis also covers other linear models such as ...
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Statistical Modelling in GLIM 4
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by
Murray Aitkin, Brian Francis, John Hinde
This new edition of the successful multi-disciplinary text Statistical Modelling in GLIM takes into account new developments in both statistical software and statistical modelling. Including three new chapters on mixture and random effects models, it provides a comprehensive treatment of the theory of statistical modelling with generalised linear ...
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Structural Equation Modeling: A Second Course (He
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by
Gregory R Hancock (Editor), Ralph O Muller (Editor)
This volume is intended to serve as a didactically-oriented resource covering a broad range of advanced topics often not discussed in introductory courses on structural equation modeling (SEM). Such topics are important in furthering the understanding of foundations and assumptions underlying SEM as well as in exploring SEM as a potential tool to ...
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Linear models a mean model approach
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by
Moser
Linear models, normally presented in a highly theoretical and mathematical style, are brought down to earth in this comprehensive textbook. "Linear Models" examines the subject from a mean model perspective, defining simple and easy-to-learn rules for building mean models, regression models, mean vectors, covariance matrices and sums of squares ...
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