Linear Models

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.

Shayle R. Searle, PhD, is Professor Emeritus in the Department of Biological Statistics and Computational Biology at Cornell University. Dr. Searle is the author of Linear Models, Linear Models for Unbalanced Data, Matrix Algebra Useful for Statistics, and Variance Components, all published by Wiley.

1. Generalized Inverse Matrices

1

(30)

2. Distributions and Quadratic Forms

31

(44)

3. Regression, or the Full Rank Model

75

(60)

4. Introducing Linear Models: Regression on Dummy Variables

135

(29)

5. Models Not of Full Rank

164

(62)

6. Two Elementary Models

226

(35)

7. The 2-Way Crossed Classification

261

(71)

8. Some Other Analyses

332

(44)

9. Introduction to Variance Components

376

(45)

10. Methods of Estimating Variance Components from Unbalanced Data

421

(52)

11. Variance Component Estimation from Unbalanced Data: Formulae

473

(42)

Literature Cited

515

(8)

Statistical Tables

523

(6)

Index

529

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Summary

Author Biography

Table of Contents

Supplemental Materials