Detection theory: A user's guide, 2nd ed.

By N. Macmillan, C. D. Creelman. 2005

2,053 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2f6d45f0a18fc99e8cedd35d261691f12eca1700

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Citations in the corpus

Color constancy. (2011, unknown): “Randomization of the surround affected subjects' criteria, but not their discrimination performance d' from signal-detection theory (Macmillan & Creelman, 2005) nor their constancy indices.”
Dual-process theory and signal-detection theory of recognition memory. (2007, background): “It replaced an earlier theory, one that was simple and intuitively compelling, known as high-threshold theory (Green & Swets, 1966; Macmillan & Creelman , 2005).”
On the Analysis of Fraction Subtraction Data: The DINA Model, Classification, Latent Class Sizes, and the Q-Matrix (2011, methodology): “Using terminology from signal detection theory (e.g., Macmillan & Creelman, 2005), gj is the probability of a false alarm, 1 – sj is the probability of a hit, and sj is the probability of a miss. Note that the notion of guessing is simply an interpretation of the false alarm rate.”
The effect of stimulus strength on the speed and accuracy of a perceptual decision. (2005, background): “The modern starting point is signal detection theory (Green & Swets, 1966; Macmillan & Creelman, 2005).”
Methodological and empirical developments for the Ratcliff diffusion model of response times and accuracy (2009, result): “Note that, in contrast to signal-detection theory (Macmillan & Creelman, 2005), the participant is assumed to base a decision not on a single noisy sample, but on an entire sequence of noisy samples.”
Prefrontal contributions to metacognition in perceptual decision-making (2012, methodology): “The fit of the type 2 SDT model was assessed via the following linear regression model (Macmillan and Creelman, 2005): z h 0 1z f .”
Memory is More than just Remembering: Strategic Control of Encoding, Accessing Memory, and Making Decisions (2007, background): “…are derived from yes/no tasks are known to be inadequate because they fail to explicitly account for greater variance in the probability distribution in the strengths of studied than unstudied items (Macmillan & Creelman, 2005), as are ''nonparametric'' variants of those values (Benjamin, 2005a).”
An EZ-diffusion model for response time and accuracy (2007, background): “Several solutions have been proposed to address this issue (see, e.g., Macmillan & Creelman, 2004).”
The natural/man-made distinction is made before basic-level distinctions in scene gist processing (2010, background): “Though a correlation between sensitivity and bias is contrary to a basic tenet of detection theory (Macmillan & Creelman, 2005), negative correlations of an even greater magnitude between sensitivity and bias measures (d? and c) have previously been reported (See, Warm, Dember, & Howe, 1997).”
Self-Evaluation of Decision-Making: A General Bayesian Framework for Metacognitive Computation (2017, background): “…in signal detection theoretic models, the absolute distance of the decision variable from a criterion is a proxy for confidence (Cart-wright & Festinger, 1943; Ferrell & McGoey, 1980; Kepecs et al., 2008; Macmillan & Creelman, 2005; Suantak, Bolger, & Ferrell, 1996; Treisman & Faulkner, 1984).”
Synthesis and evaluation of linear motion transitions (2008, background): “This somewhat cumbersome de sign is necessary to make a two-alternative forced choice test with an objective answer that best eliminates response bias and crite rion effects [MacMillan and Creelman 2004].”