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  • © 2020

Plane Answers to Complex Questions

The Theory of Linear Models

  • Features exercises throughout, with additional exercises supplied at the end of each chapter so that readers can retain theory
  • Illustrates the practical application of the projective approach to linear models
  • Includes appendices that with prerequisite background information on linear algebra and mathematical statistics
  • Prepared in conjunction with a new edition of Christensen's Advanced Linear Modeling, so that advanced undergraduate and graduate students have access to a wealth of revised content in statistical theory
  • Provides access to accompanying computer code
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Texts in Statistics (STS)

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xxii
  2. Introduction

    • Ronald Christensen
    Pages 1-20
  3. Estimation

    • Ronald Christensen
    Pages 21-60
  4. Testing

    • Ronald Christensen
    Pages 61-105
  5. One-Way ANOVA

    • Ronald Christensen
    Pages 107-121
  6. Multiple Comparison Techniques

    • Ronald Christensen
    Pages 123-143
  7. Regression Analysis

    • Ronald Christensen
    Pages 145-195
  8. Multifactor Analysis of Variance

    • Ronald Christensen
    Pages 197-240
  9. Experimental Design Models

    • Ronald Christensen
    Pages 241-254
  10. Analysis of Covariance

    • Ronald Christensen
    Pages 255-279
  11. General Gauss–Markov Models

    • Ronald Christensen
    Pages 281-311
  12. Split Plot Models

    • Ronald Christensen
    Pages 313-339
  13. Model Diagnostics

    • Ronald Christensen
    Pages 341-391
  14. Collinearity and Alternative Estimates

    • Ronald Christensen
    Pages 393-417
  15. Variable Selection

    • Ronald Christensen
    Pages 419-446
  16. Back Matter

    Pages 447-529

About this book

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 exercises and examples that make it ideal for a graduate-level course. All of the standard topics are covered in depth: estimation including biased and Bayesian estimation, significance testing, ANOVA, multiple comparisons, regression analysis, and experimental design models.  In addition, the book covers topics that are not usually treated at this level, but which are important in their own right: best linear and best linear unbiased prediction, split plot models, balanced incomplete block designs, testing for lack of fit, testing for independence, models with singular covariance matrices, diagnostics, collinearity, and variable selection. This new edition includes new sections on alternatives to least squares estimation and the variance-bias tradeoff, expanded discussion of variable selection, new material on characterizing the interaction space in an unbalanced two-way ANOVA, Freedman's critique of the sandwich estimator, and much more.

Authors and Affiliations

  • Department of Mathematics and Statistics, University of New Mexico, Albuquerque, USA

    Ronald Christensen

About the author

Ronald Christensen is a Professor of Statistics at the University of New Mexico, Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics, former Chair of the ASA Section on Bayesian Statistical Science and former Editor of The American Statistician. His book publications include Advanced Linear Modeling (Springer, new edition forthcoming), Log-Linear Models and Logistic Regression (Springer 1997), Analysis of Variance, Design, and Regression (1996, 2016), and  Bayesian Ideas and Data Analysis (2010, with Johnson, Branscum and Hanson).

Bibliographic Information

  • Book Title: Plane Answers to Complex Questions

  • Book Subtitle: The Theory of Linear Models

  • Authors: Ronald Christensen

  • Series Title: Springer Texts in Statistics

  • DOI: https://doi.org/10.1007/978-3-030-32097-3

  • Publisher: Springer Cham

  • eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)

  • Copyright Information: Springer Nature Switzerland AG 2020

  • Hardcover ISBN: 978-3-030-32096-6Published: 13 March 2020

  • Softcover ISBN: 978-3-030-32099-7Published: 26 August 2021

  • eBook ISBN: 978-3-030-32097-3Published: 13 March 2020

  • Series ISSN: 1431-875X

  • Series E-ISSN: 2197-4136

  • Edition Number: 5

  • Number of Pages: XXII, 529

  • Number of Illustrations: 33 b/w illustrations

  • Topics: Statistical Theory and Methods

Buy it now

Buying options

eBook USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access