FRONT COVER	1
	PSYCHOPHYSICS: A PRACTICAL INTRODUCTION	4
	COPYRIGHT PAGE	5
	CONTENTS	8
	PREFACE	12
	ACKNOWLEDGEMENTS	14
	ABOUT THE AUTHORS	16
	CHAPTER 1. INTRODUCTION AND AIMS	18
	1.1 What is Psychophysics?	18
	1.2 Aims of the Book	19
	1.3 Organization of the Book	19
	1.4 Introducing Palamedes	20
	1.4.1 Organization of Palamedes	22
	1.4.2 Functions and Demonstration Programs in Palamedes	23
	1.4.3 Error Messages in Palamedes	25
	References	25
	CHAPTER 2. CLASSIFYING PSYCHOPHYSICAL EXPERIMENTS	26
	2.1 Introduction	26
	2.2 Tasks, Methods, and Measures	27
	2.3 Dichotomies	30
	2.3.1 "Class A" Versus "Class B" Observations	30
	2.3.2 "Objective" Versus "Subjective"	35
	2.3.3 "Type 1" Versus "Type 2"	38
	2.3.4 "Performance" Versus "Appearance"	39
	2.3.5 "Forced-choice" Versus "Non-forced-choice"	43
	2.3.6 "Criterion-free" Versus "Criterion-dependent"	46
	2.3.7 "Detection" Versus "Discrimination"	47
	2.3.8 "Threshold" Versus "Suprathreshold"	49
	2.4 Classification Scheme	50
	Further Reading	51
	Exercises	52
	References	52
	CHAPTER 3. VARIETIES OF PSYCHOPHYSICAL PROCEDURE	56
	3.1 Introduction	56
	3.2 Performance-Based Procedures	58
	3.2.1 Thresholds	58
	3.2.2 Non-threshold Tasks Procedures	65
	3.3 Appearance-Based Procedures	65
	3.3.1 Matching	65
	3.3.2 Scaling	68
	3.4 Further Design Details	73
	3.4.1 Method of Constant Stimuli	73
	3.4.2 Adaptive Procedures	73
	3.4.3 Timing of Stimulus Presentation	74
	Further Reading	75
	References	75
	CHAPTER 4. PSYCHOMETRIC FUNCTIONS	76
	4.1 Introduction	76
	4.2 Section A: Practice	77
	4.2.1 Overview of the Psychometric Function	77
	4.2.2 Number of Trials and Stimulus Levels	78
	4.2.3 Types and Choice of Function	81
	4.2.4 Methods for Fitting Psychometric Functions	85
	4.2.5 Estimating the Errors	87
	4.2.6 Estimating the Goodness-of-Fit	89
	4.2.7 Putting it All Together	90
	4.3 Section B: Theory and Details	91
	4.3.1 Psychometric Function Theories	91
	4.3.2 Details of Function Types	98
	4.3.3 Methods for Fitting Psychometric Functions	102
	Further Reading	135
	Exercises	135
	References	135
	CHAPTER 5. ADAPTIVE METHODS	138
	5.1 Introduction	138
	5.2 Up/Down Methods	139
	5.2.1 Up/Down Method	139
	5.2.2 Transformed Up/Down Method	141
	5.2.3 Weighted Up/Down Method	142
	5.2.4 Transformed and Weighted Up/Down Method	144
	5.2.5 Termination Criteria and the Threshold Estimate	144
	5.2.6 Up/Down Methods in Palamedes	145
	5.2.7 Some Practical Tips	149
	5.3 "Running Fit" Methods: The Best Pest and Quest	152
	5.3.1 The Best PEST	152
	5.3.2 Quest	154
	5.3.3 Termination Criteria and Threshold Estimate	155
	5.3.4 Running Fit Methods in Palamedes	155
	5.3.5 Some Practical Tips	158
	5.4 Psi Method	160
	5.4.1 The Psi Method	160
	5.4.2 Termination Criteria and the Threshold and Slope Estimates	164
	5.4.3 The Psi Method in Palamedes	165
	5.4.4 Some Practical Tips	166
	Exercises	167
	References	167
	CHAPTER 6. SIGNAL DETECTION MEASURES	170
	6.1 Introduction	171
	6.1.1 What is Signal Detection Theory (SDT)?	171
	6.1.2 A Recap on Some Terminology: N, m and M	171
	6.1.3 Why Measure d'?	173
	6.2 Section A: Practice	175
	6.2.1 Signal Detection Theory with Palamedes	175
	6.2.2 Converting Pc to d' for Unbiased M-AFC Tasks	176
	6.2.3 Measuring d' for 1AFC Tasks	177
	6.2.4 Measuring d' for 2AFC Tasks with Observer Bias	180
	6.2.5 Measuring d' for Same-Different Tasks	181
	6.2.6 Measuring d' for Match-to-Sample Tasks	184
	6.2.7 Measuring d' for M-AFC Oddity Tasks	185
	6.2.8 Estimating Pc[sub(max)] with Observer Bias	186
	6.2.9 Comparing d's and Pcs across Different Tasks	186
	6.3 Section B: Theory	187
	6.3.1 Relationship Between Z-scores and Probabilities	187
	6.3.2 Calculation of d' for M-AFC	189
	6.3.3 Calculation of d' and Measures of Bias for 1AFC Tasks	191
	6.3.4 Calculation of d' for Unbiased and Biased 2AFC Tasks	195
	6.3.5 Calculation of d' for Same-Different Tasks	198
	6.3.6 Calculation of d' for Match-to-Sample Tasks	203
	6.3.7 Calculation of d' for M-AFC Oddity Tasks	204
	Further Reading	205
	Exercises	205
	References	206
	CHAPTER 7. SCALING METHODS	208
	7.1 Introduction	208
	7.2 Section A: Practice	210
	7.2.1 Maximum Likelihood Difference Scaling (MLDS)	210
	7.3 Section B: Theory	217
	7.3.1 How MLDS Works	217
	7.3.2 Perceptual Scales and Internal Noise	219
	7.3.3 Partition Scaling	222
	Further Reading	224
	Exercise	224
	CHAPTER 8. MODEL COMPARISONS	226
	8.1 Introduction	226
	8.2 Section A: Statistical Inference	229
	8.2.1 Standard Error Eyeballing	229
	8.2.2 Model Comparisons	232
	8.2.3 Other Model Comparisons	240
	8.2.4 Goodness-of-Fit	243
	8.2.5 More Than Two Conditions	246
	8.3 Section B: Theory and Details	253
	8.3.1 The Likelihood Ratio Test	253
	8.3.2 Simple Example: Fairness of Coin	253
	8.3.3 Composite Hypotheses	256
	8.3.4 Specifying Models Using Contrasts	259
	8.3.5 A Note on Failed Fits	266
	8.4 Some Alternative Model Comparison Methods	267
	8.4.1 Information Criteria: AIC and BIC	267
	8.4.2 Bayes Factor and Posterior Odds	270
	Further Reading	271
	Exercises	271
	References	272
	QUICK REFERENCE GUIDE	274
	ACRONYMS	290
	INDEX	292
	A	292
	B	293
	C	293
	D	293
	F	293
	G	293
	H	293
	I	293
	J	293
	L	293
	M	293
	N	294
	O	294
	P	294
	Q	295
	R	295
	S	295
	T	296
	U	296
	W	296
	Z	296
	COLOR PLATES	297