Search Results for "applied-regression-analysis-and-generalized-linear-models"

Applied Regression Analysis and Generalized Linear Models

Applied Regression Analysis and Generalized Linear Models

  • Author: John Fox
  • Publisher: SAGE Publications
  • ISBN: 1483321312
  • Category: Social Science
  • Page: 816
  • View: 6587
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Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book.

Applied Regression Analysis, Linear Models, and Related Methods

Applied Regression Analysis, Linear Models, and Related Methods

  • Author: John Fox
  • Publisher: SAGE
  • ISBN: 9780803945401
  • Category: Social Science
  • Page: 597
  • View: 6308
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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 research. It then moves on to cover the following topics: graphical methods for examining and transforming data; linear least-squares regression; dummy-variables regression; analysis of variance; diagnostic methods for discovering whether a linear model fit to data adequately represents the data; extensions to linear least squares, including logit and probit models, time-series regression, nonlinear

Applied Regression Analysis and Generalized Linear Models

Applied Regression Analysis and Generalized Linear Models

  • Author: John Fox
  • Publisher: SAGE Publications
  • ISBN: 1483386473
  • Category: Social Science
  • Page: 816
  • View: 8021
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Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book.

Applied Regression Analysis and Generalized Linear Models

Applied Regression Analysis and Generalized Linear Models

  • Author: John Fox
  • Publisher: SAGE Publications, Incorporated
  • ISBN: 9780761930426
  • Category: Social Science
  • Page: 688
  • View: 8143
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Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Second Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material throughout the book. Key Updates to the Second Edition: Provides greatly enhanced coverage of generalized linear models, with an emphasis on models for categorical and count data Offers new chapters on missing data in regression models and on methods of model selection Includes expanded treatment of robust regression, time-series regression, nonlinear regression, and nonparametric regression Incorporates new examples using larger data sets Includes an extensive Web site at http://www.sagepub.com/fox that presents appendixes, data sets used in the book and for data-analytic exercises, and the data-analytic exercises themselves Intended Audience: This core text will be a valuable resource for graduate students and researchers in the social sciences (particularly sociology, political science, and psychology) and other disciplines that employ linear and related models for data analysis.

An R Companion to Applied Regression

An R Companion to Applied Regression

  • Author: John Fox,Sanford Weisberg
  • Publisher: SAGE Publications
  • ISBN: 141297514X
  • Category: Social Science
  • Page: 449
  • View: 4234
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This book aims to provide a broad introduction to the R statistical environment in the context of applied regression analysis, which is typically studied by social scientists and others in a second course in applied statistics.

An R and S-Plus Companion to Applied Regression

An R and S-Plus Companion to Applied Regression

  • Author: John Fox
  • Publisher: SAGE
  • ISBN: 9780761922803
  • Category: Mathematics
  • Page: 312
  • View: 936
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"This book fits right into a needed niche: rigorous enough to give full explanation of the power of the S language, yet accessible enough to assign to social science graduate students without fear of intimidation. It is a tremendous balance of applied statistical "firepower" and thoughtful explanation. It meets all of the important mechanical needs: each example is given in detail, code and data are freely available, and the nuances of models are given rather than just the bare essentials. It also meets some important theoretical needs: linear models, categorical data analysis, an introduction to applying GLMs, a discussion of model diagnostics, and useful instructions on writing customized functions. " —JEFF GILL, University of Florida, Gainesville

Regression Diagnostics

Regression Diagnostics

An Introduction

  • Author: John Fox
  • Publisher: SAGE
  • ISBN: 9780803939714
  • Category: Mathematics
  • Page: 92
  • View: 3358
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With Regression Diagnostics, researchers now have an accessible explanation of the techniques needed for exploring problems that compromise a regression analysis and for determining whether certain assumptions appear reasonable. The book covers such topics as the problem of collinearity in multiple regression, dealing with outlying and influential data, non-normality of errors, non-constant error variance and the problems and opportunities presented by discrete data. In addition, sophisticated diagnostics based on maximum-likelihood methods, scores tests, and constructed variables are introduced.

Interaction Effects in Linear and Generalized Linear Models

Interaction Effects in Linear and Generalized Linear Models

Examples and Applications Using Stata

  • Author: Robert L. Kaufman
  • Publisher: SAGE Publications
  • ISBN: 1506365396
  • Category: Social Science
  • Page: 608
  • View: 3872
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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 (downloadable from the Robert L. Kaufman’s website), 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 data sets and the Stata code to reproduce the results of the application examples are available online.

Applied Regression Including Computing and Graphics

Applied Regression Including Computing and Graphics

  • Author: R. Dennis Cook,Sanford Weisberg
  • Publisher: John Wiley & Sons
  • ISBN: 0470317787
  • Category: Mathematics
  • Page: 632
  • View: 6037
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A step-by-step guide to computing and graphics in regression analysis In this unique book, leading statisticians Dennis Cook and Sanford Weisberg expertly blend regression fundamentals and cutting-edge graphical techniques. They combine and up- date most of the material from their widely used earlier work, An Introduction to Regression Graphics, and Weisberg's Applied Linear Regression; incorporate the latest in statistical graphics, computing, and regression models; and wind up with a modern, fully integrated approach to one of the most important tools of data analysis. In 23 concise, easy-to-digest chapters, the authors present:? A wealth of simple 2D and 3D graphical techniques, helping visualize results through graphs * An improved version of the user-friendly Arc software, which lets readers promptly implement new ideas * Complete coverage of regression models, including logistic regression and generalized linear models * More than 300 figures, easily reproducible on the computer * Numerous examples and problems based on real data * A companion Web site featuring free software and advice, available at www.wiley.com/mathem atics Accessible, self-contained, and fully referenced, Applied Regression Including Computing and Graphics assumes only a first course in basic statistical methods and provides a bona fide user manual for the Arc software. It is an invaluable resource for anyone interested in learning how to analyze regression problems with confidence and depth.

Multiple and Generalized Nonparametric Regression

Multiple and Generalized Nonparametric Regression

  • Author: John Fox
  • Publisher: SAGE
  • ISBN: 9780761921899
  • Category: Social Science
  • Page: 83
  • View: 3795
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This book builds on John Fox's previous volume in the QASS Series, Non Parametric Simple Regression. In this book, the reader learns how to estimate and plot smooth functions when there are multiple independent variables.