Preface |
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xiv | |
Introduction |
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xvii | |
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PART I Basic Detection Theory and One-Interval Designs |
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1 | (136) |
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1 The Yes-No Experiment: Sensitivity |
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3 | (24) |
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Understanding Yes-No Data |
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3 | (5) |
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Implied Receiver Operating Characteristics |
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8 | (6) |
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The Signal-Detection Model |
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14 | (3) |
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17 | (1) |
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Essay: The Provenance of Detection Theory |
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18 | (2) |
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20 | (1) |
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20 | (1) |
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21 | (1) |
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22 | (2) |
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24 | (3) |
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2 The Yes-No Experiment: Response Bias |
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27 | (27) |
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27 | (1) |
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28 | (4) |
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Alternative Measures of Bias |
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32 | (2) |
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34 | (1) |
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Experimental Manipulation of Bias |
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35 | (2) |
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Comparing the Bias Measures |
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37 | (5) |
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How Does the Participant Choose a Decision Rule? |
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42 | (2) |
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Calculating Hit and False-Alarm Rates from Parameters |
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44 | (1) |
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Variability of Decision Criteria |
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45 | (1) |
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Essay: On Human Decision-Making |
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45 | (1) |
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46 | (1) |
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47 | (1) |
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47 | (1) |
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48 | (3) |
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51 | (3) |
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3 Beyond Binary Responses: The Rating Experiment and Empirical |
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Receiver Operating Characteristics |
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54 | (1) |
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Design of Rating Experiments |
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54 | (1) |
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Receiver Operating Characteristic Analysis |
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55 | (2) |
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Relationship between Binary and Rating Responses |
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57 | (9) |
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ROC Analysis with Slopes Other Than 1 |
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59 | |
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66 | (3) |
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Systematic Parameter Estimation and Methods of Calculation |
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69 | (2) |
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Alternative Ways to Generate ROCs |
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71 | (4) |
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Another Kind of ROC: Type 2 |
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72 | |
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Essay: Are ROCs Necessary? |
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75 | (2) |
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77 | (1) |
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77 | (1) |
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78 | (1) |
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79 | (4) |
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83 | (2) |
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4 Classification Experiments for One-Dimensional Stimulus Sets |
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85 | (24) |
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Design of Classification Experiments |
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85 | (1) |
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Perceptual One-Dimensionality |
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85 | (2) |
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Two-Response Classification |
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87 | (9) |
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Experiments with More Than Two Responses |
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96 | (3) |
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99 | (1) |
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Comparing Classification and Discrimination |
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100 | (2) |
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102 | (1) |
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103 | (3) |
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106 | (3) |
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5 Threshold Models and Choice Theory |
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109 | (28) |
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Single High-Threshold Theory |
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110 | (3) |
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113 | (2) |
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Double High-Threshold Theory |
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115 | (4) |
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119 | (6) |
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Measures Based on Areas in ROC Space: Unintentional Applications of Choice Theory |
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125 | (3) |
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Nonparametric Analysis of Rating Data |
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128 | (1) |
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Essay: The Appeal of Discrete Models |
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128 | (2) |
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130 | (1) |
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131 | (1) |
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132 | (2) |
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134 | (3) |
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PART II Multidimensional Detection Theory and Multi-Interval Discrimination Designs |
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137 | (114) |
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6 Detection and Discrimination of Compound Stimuli: Tools for Multidimensional Detection Theory |
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139 | (19) |
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Distributions in One- and Two-Dimensional Spaces |
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140 | (5) |
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Some Characteristics of Two-Dimensional Spaces |
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145 | (3) |
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148 | (6) |
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Inferring the Representation from Data |
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154 | (2) |
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156 | (1) |
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156 | (1) |
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157 | (1) |
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7 Comparison (Two-Distribution) Designs for Discrimination |
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158 | (26) |
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Two-Alternative Forced-Choice |
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158 | (13) |
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171 | (2) |
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Two-Alternative Forced-Choice Reminder |
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173 | (2) |
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175 | (2) |
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Essay: Psychophysical Comparisons and Comparison Designs |
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177 | (1) |
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177 | (1) |
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178 | (1) |
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178 | (3) |
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181 | (3) |
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8 Classification Designs: Attention and Interaction |
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184 | (22) |
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One-Dimensional Representations and Uncertainty |
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185 | (2) |
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Two-Dimensional Representations |
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187 | (4) |
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Two-Dimensional Models for Extrinsic Uncertain Detection |
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191 | (3) |
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Uncertain Simple and Compound Detection |
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194 | (2) |
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Selective- and Divided-Attention Tasks |
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196 | (3) |
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Attention Operating Characteristics |
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199 | (2) |
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201 | (1) |
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201 | (3) |
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204 | (2) |
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9 Classification Designs for Discrimination |
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206 | (25) |
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207 | (12) |
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219 | (5) |
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224 | (2) |
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226 | (1) |
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226 | (1) |
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227 | (2) |
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229 | (2) |
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10 Identification of Multidimensional Objects and Multiple Observation Intervals |
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231 | (20) |
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231 | (3) |
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Interval Identification: m-Altemative Forced-Choice |
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234 | (3) |
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Comparisons among Discrimination Paradigms |
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237 | (3) |
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Simultaneous Detection and Identification |
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240 | (3) |
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Using Identification to Test for Perceptual Interaction |
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243 | (3) |
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Essay: How to Choose an Experimental Design |
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246 | (1) |
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247 | (1) |
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248 | (1) |
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249 | (2) |
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PART III Stimulus Factors |
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251 | (46) |
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11 Adaptive Methods for Estimating Empirical Thresholds |
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253 | (27) |
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254 | (1) |
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The Tracking Algorithm: Choices for the Adaptive Tester |
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255 | (1) |
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255 | (15) |
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Evaluation of Tracking Algorithms |
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270 | (2) |
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Two More Choices: Discrimination Paradigm and the Issue of Slope |
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272 | (2) |
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274 | (1) |
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274 | (3) |
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277 | (3) |
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12 Components of Sensitivity |
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280 | (17) |
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Stimulus Determinants of d' in One Dimension |
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281 | (4) |
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Basic Processes in Multiple Dimensions |
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285 | (6) |
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291 | (1) |
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Essay: Psychophysics versus Psychoacoustics (etc.) |
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292 | (1) |
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293 | (1) |
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293 | (2) |
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295 | (2) |
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297 | (32) |
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13 Statistics and Detection Theory |
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299 | (30) |
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Hit and False-Alarm Rates |
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300 | (3) |
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Sensitivity and Bias Measures |
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303 | (12) |
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Sensitivity Estimates Based on Averaged Data |
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315 | (6) |
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Systematic Statistical Frameworks for Detection Theory |
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321 | (3) |
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324 | (1) |
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324 | (1) |
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325 | (2) |
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327 | (2) |
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Appendix 1 Elements of Probability and Statistics |
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329 | (11) |
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329 | (7) |
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336 | (3) |
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339 | (1) |
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Appendix 2 Logarithms and Exponentials |
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340 | (2) |
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Appendix 3 Flowcharts to Sensitivity and Bias Calculations |
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342 | (5) |
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Chart 1 Guide to Subsequent Charts |
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342 | (1) |
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Chart 2 Yes-No Sensitivity |
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342 | (1) |
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Chart 3 Yes-No Response Bias |
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343 | (1) |
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Chart 4 Rating-Design Sensitivity |
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343 | (1) |
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Chart 5 Definitions of Multi-Interval Designs |
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344 | (1) |
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Chart 6 Multi-Interval Sensitivity |
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344 | (1) |
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Chart 7 Multi-Interval Bias |
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345 | (1) |
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345 | (1) |
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346 | (1) |
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Appendix 4 Some Useful Equations |
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347 | (8) |
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Yes-No (Equal-Variance Signal Detection Theory) |
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347 | (1) |
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348 | (1) |
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Yes-No (Unequal-Variance Signal Detection Theory) |
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349 | (1) |
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Threshold and "Nonparametric" |
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350 | (1) |
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One-Dimensional Classification |
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350 | (1) |
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Forced-Choice (Two-Alternative Forced-Choice) |
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351 | (1) |
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Forced-Choice (m-Altemative Forced-Choice) |
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352 | (1) |
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352 | (1) |
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352 | (1) |
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353 | (1) |
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353 | (2) |
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355 | (38) |
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A5.1 Normal Distribution (p to z) |
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356 | (1) |
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A5.2 Normal Distribution (z to p) Given z, Find Φ(z), the Proportion Less Than z |
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357 | (2) |
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A5.3 Values of d' for Same-Different (Independent-Observation Model) and ABX (Independent-Observation and Difference Models) |
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359 | (12) |
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A5.4 Values of d' for Same-Different (Difference Model) |
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371 | (13) |
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A5.5 Values of 6! for Oddity, Gaussian Model (M = Number of Intervals) |
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384 | (4) |
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A5.6 Values of p(c) given A' for Oddity (Difference and Independent-Observation Model, Normal), and form AFC |
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388 | (1) |
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A5.7 Values of d' for m-Interval Forced Choice or Identification |
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389 | (3) |
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392 | (1) |
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Appendix 6 Software for Detection Theory |
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393 | (2) |
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393 | (1) |
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394 | (1) |
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394 | (1) |
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Appendix 7 Solutions to Selected Problems |
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395 | (18) |
Glossary |
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413 | (11) |
Index |
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424 | |