Preface

Acknowledgements

About the Authors

1. Introduction and Aims

1.1 What is Psychophysics?

1.2 Aims of the Book

1.3 Organization of the Book

1.4 Introducing Palamedes

1.4.1 Organization of Palamedes

1.4.2 Functions and Demonstration Programs in Palamedes

1.4.3 Error Messages in Palamedes

References

2. Classifying Psychophysical Experiments

2.1 Introduction

2.2 Tasks, Methods, and Measures

2.3 Dichotomies

2.3.1 "Class A" versus "Class B" Observations

2.3.2 "Objective" versus "Subjective"

2.3.3 "Type 1" versus "Type 2"

2.3.4 "Performance" versus "Appearance"

2.3.5 "Forced-choice" versus "Non-forced-choice"

2.3.6 "Criterion-free" versus "Criterion-dependent"

2.3.7 "Detection" versus "Discrimination"

2.3.8 "Threshold" versus "Suprathreshold"

2.4 Classification Scheme

Further Reading

Exercises

References

3. Varieties of Psychophysical Procedure

3.1 Introduction

3.2 Performance-Based Procedures

3.2.1 Thresholds

3.2.2 Non-threshold Tasks Procedures

3.3 Appearance-Based Procedures

3.3.1 Matching

3.3.2 Scaling

3.4 Further Design Details

3.4.1 Method of Constant Stimuli

3.4.2 Adaptive Procedures

3.4.3 Timing of Stimulus Presentation

Further Reading

References

4. Psychometric Functions

4.1 Introduction

4.2 Section A: Practice

4.2.1 Overview of the Psychometric Function

4.2.2 Number of Trials and Stimulus Levels

4.2.3 Types and Choice of Function

4.2.4 Methods for Fitting Psychometric Functions

4.2.5 Estimating the Errors

4.2.6 Estimating the Goodness-of-Fit

4.2.7 Putting it All Together

4.3 Section B: Theory and Details

4.3.1 Psychometric Function Theories

4.3.2 Details of Function Types

4.3.3 Methods for Fitting Psychometric Functions

Further Reading

Exercises

References

5. Adaptive Methods

5.1 Introduction

5.2 Up/Down Methods

5.2.1 Up/Down Method

5.2.2 Transformed Up/Down Method

5.2.3 Weighted Up/Down Method

5.2.4 Transformed and Weighted Up/Down Method

5.2.5 Termination Criteria and the Threshold Estimate

5.2.6 Up/Down Methods in Palamedes

5.2.7 Some Practical Tips

5.3 "Running Fit" Methods: The Best Pest and Quest

5.3.1 The Best PEST

5.3.2 Quest

5.3.3 Termination Criteria and Threshold Estimate

5.3.4 Running Fit Methods in Palamedes

5.3.5 Some Practical Tips

5.4 Psi Method

5.4.1 The Psi Method

5.4.2 Termination Criteria and the Threshold and Slope Estimates

5.4.3 The Psi Method in Palamedes

5.4.4 Some Practical Tips

Exercises

References

6. Signal Detection Measures

6.1 Introduction

6.1.1 What is Signal Detection Theory (SDT)?

6.1.2 A Recap on Some Terminology: N , m and M

6.1.3 Why Measure d’?

6.2 Section A: Practice

6.2.1 Signal Detection Theory with Palamedes

6.2.2 Converting Pc to d’ for Unbiased M-AFC Tasks

6.2.3 Measuring d’ for 1AFC Tasks

6.2.4 Measuring d’ for 2AFC Tasks with Observer Bias

6.2.5 Measuring d’ for Same-Different Tasks

6.2.6 Measuring d’ for Match-to-Sample Tasks

6.2.7 Measuring d’ for M -AFC Oddity Tasks

6.2.8 Estimating Pcmax with Observer Bias

6.2.9 Comparing d’s and Pcs across Different Tasks

6.3 Section B: Theory

6.3.1 Relationship Between Z-scores and Probabilities

6.3.2 Calculation of d’ for M-AFC

6.3.3 Calculation of d’ and Measures of Bias for 1AFC Tasks

6.3.4 Calculation of d’ for Unbiased and Biased 2AFC Tasks

6.3.5 Calculation of d’ for Same-Different Tasks

6.3.6 Calculation of d’ for Match-to-Sample Tasks

6.3.7 Calculation of d for M -AFC Oddity Tasks

Further Reading

Exercises

References

7. Scaling Methods

7.1 Introduction

7.2 Section A: Practice

7 .2.1 Maximum Likelihood Difference Scaling (MLDS)

7.3 Section B: Theory

7.3.1 How MLDS Works

7.3.2 Perceptual Scales and Internal Noise

7.3.3 Partition Scaling

Further Reading

Exercise

8. Model Comparisons

8.1 Introduction

8.2 Section A: Statistical Inference

8.2.1 Standard Error Eyeballing

8.2.2 Model Comparisons

8.2.3 Other Model Comparisons

8.2.4 Goodness-of-Fit

8.2.5 More Than Two Conditions

8.3 Section B: Theory and Details

8.3.1 The Likelihood Ratio Test

8.3.2 Simple Example: Fairness of Coin

8.3.3 Composite Hypotheses

8.3.4 Specifying Models Using Contrasts

8.3.5 A Note on Failed Fits

8.4 Some Alternative Model Comparison Methods

8.4.1 Information Criteria: AIC and BIC

8.4.2 Bayes Factor and Posterior Odds

Further Reading

Exercises

References

Quick Reference Guide

Acronyms

Index