SAS System for Regression

This book describes how to use the SAS System to perform a wide variety of different regression analyses, such as using various models as well as diagnosing data problems. Topics include performing linear regression analyses using PROC REG; diagnosing and providing remedies for data problems including outliers and multicollinearity; using regression to fit a variety of different models, including nonlinear models; using SAS/INSIGHT software for performing regression analysis. Examples feature many SAS procedures including REG, PLOT, GPLOT, NLIN, RSREG, AUTOREG, PRINCOMP, and others.

Rudolf Freund is Professor Emeritus, Texas A&M University.

Ramon Littell is at the University of Florida.

Acknowledgments

vii

Regression Concepts

1

(14)

Statistical Background

1

(8)

Performing a Regression with the IML Procedure

9

(3)

Regression with the SAS System

12

(3)

Using the REG Procedure

15

(48)

Introduction

15

(2)

A Model with One Independent Variable

17

(3)

A Model with Several Independent Variables

20

(4)

Various Model Statement Options

24

(12)

Further Examination of Model Parameters

36

(7)

Plotting Results

43

(9)

Creating Data I: the Output Statement

52

(3)

Creating Data II: Other Data Sets

55

(2)

Creating Data III: ODS Output

57

(1)

Predicting to a Different Set of Data

57

(3)

Exact Collinearity: Linear Dependency

60

(2)

Summary

62

(1)

Observations

63

(32)

Introduction

63

(1)

Outlier Detection

64

(13)

Specification Errors

77

(4)

Heterogeneous Variances

81

(5)

Correlated Errors

86

(8)

Summary

94

(1)

Multicollinearity: Detection and Remedial Measures

95

(32)

Introduction

95

(2)

Detecting Multicollinearity

97

(4)

Model Restructuring

101

(7)

Variable Selection

108

(12)

Biased Estimation

120

(5)

Summary

125

(2)

Curve Fitting

127

(30)

Introduction

127

(1)

Polynomial Models with One Independent Variable

128

(4)

Polynomial Plots

132

(2)

Polynomial Models with Several Variables

134

(4)

Response Surface Plots

138

(4)

A Three-Factor Response Surface Experiment

142

(6)

Curve Fitting without a Model

148

(7)

Summary

155

(2)

Special Applications of Linear Models

157

(28)

Introduction

157

(1)

Multiplicative Models

158

(6)

Spline Models

164

(5)

Indicator Variables

169

(4)

Binary Response Variable: Logistic Regression

173

(11)

Summary

184

(1)

Nonlinear Models

185

(22)

Introduction

185

(1)

Estimating the Exponential Decay Model

186

(6)

Fitting a Growth Curve with the NLIN Procedure

192

(6)

Fitting Splines with Unknown Knots

198

(5)

Additional Comments on the NLIN Procedure

203

(1)

Summary

204

(3)

Using SAS/Insight Software for Regression

207

(20)

Introduction

207

(1)

Multiple Linear Regression: the BOQ Data

207

(8)

A Polynomial Response Surface: the FISH Data

215

(3)

Logistic Regression: the DYSTRO Data

218

(3)

Nonparametric Smoothing: the Barbados Data

221

(4)

Summary

225

(2)

References

227

(2)

Index

229

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SAS System for Regression

Summary

Author Biography

Table of Contents

Supplemental Materials