Contents

Preface

Acknowledgments

Chapter 1  Introduction

1.1 About Receiver Operating Characteristic Curves

1.2 Summary of Chapters

Chapter 2  Single Binary Predictor

2.1 Introduction

2.2 Frost Forecast Example

2.3 Misclassification Rate

2.4 Sensitivity and Specificity

2.5 Computations Using PROC FREQ

Chapter 3  Single Continuous Predictor

3.1 Dichotomizing a Continuous Predictor

3.2 The ROC Curve

3.3 Empirical ROC Curve and the Conditional Distributions of the Marker

3.4 Area under the ROC Curve

3.5 Selecting an Optimal Threshold

3.6 The Binormal ROC Curve

3.7 Transformations to Binormality

3.8 Direct Estimation of the Binormal ROC Curve

3.9 Bootstrap Confidence Intervals for the Area under the Curve

Chapter 4  Comparison and Covariate Adjustment of ROC Curves

4.1 Introduction

4.2 An Example from Prostate Cancer Prognosis

4.3 Paired versus Unpaired Comparisons

4.4 Comparing the Areas under the Empirical ROC Curves

4.5 Comparing the Binormal ROC Curves

4.6 Discrepancy between Binormal and Empirical ROC Curves

4.7 Bootstrap Confidence Intervals for the Difference in the Area under the Empirical ROC Curve

4.8 Covariate Adjustment for ROC Curves

4.9 Regression Model for the Binormal ROC Curve

Chapter 5  Ordinal Predictors

5.1 Introduction

5.2 Credit Rating Example

5.3 Empirical ROC Curve for Ordinal Predictors

5.4 Area under the Empirical ROC Curve

5.5 Latent Variable Model

5.6 Comparing ROC Curves for Ordinal Markers

Chapter 6  Lehmann Family of ROC Curves

6.1 Introduction

6.2 Lehmann Family of Distributions

6.3 Magnetic Resonance Example

6.4 Adjusting for Covariates

6.5 Using Estimating Equations to Handle Clustered Data

6.6 Comparing Markers Using the Lehmann Family of ROC Curves

6.7 Advantages and Disadvantages of the Lehmann Family of ROC Curves

Chapter 7  ROC Curves with Censored Data

7.1 Introduction

7.2 Lung Cancer Example

7.3 ROC Curves with Censored Data

7.4 Concordance Probability with Censored Data

7.5 Concordance Probability and the Cox Model

Chapter 8  Using the ROC Curve to Evaluate Multivariable Prediction Models

8.1 Introduction

8.2 Liver Surgery Example

8.3 Resubstitution Estimate of the ROC Curve

8.4 Split-Sample Estimates of the ROC Curve

8.5 Cross-Validation Estimates of the ROC Curve

8.6 Bootstrap-Validated Estimates of the ROC Curve

Chapter 9  ROC Curves in SAS Enterprise Miner

9.1 Introduction

9.2 Home Equity Loan Example

9.3 ROC Curves from SAS Enterprise Miner for a Single Model

9.4 ROC Curves from SAS Enterprise Miner for Competing Models

9.5 ROC Curves Using PROC GPLOT with Exported Data from SAS Enterprise Miner

Appendix  An Introduction to PROC NLMIXED

A.1 Fitting a Simple Linear Model: PROC GLM vs PROC NLMIXED

A.2 PROC NLMIXED and the Binormal Model

References

Index

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