Perceptual interactions of facial dimensions in speeded classification and identification

Thomas, Robin D.

doi:10.3758/bf03194426

Cited by 49 publications

(104 citation statements)

References 53 publications

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“…Hence, we do not define it here or explain its role in GRT in any more detail. Interested readers are referred to the original publications (e.g., Ashby & Townsend, 1986) or more recent applications (Thomas, 2001a(Thomas, , 2001bValdez & Amazeen, 2008). separability and mean shift integrality is empirically equivalent to a model with perceptual separability and a failure of decisional separability.…”

Section: Decisional Separability and Model Identification In Gaussianmentioning

confidence: 99%

“…Namely, there are tests of marginal response invariance (e.g., Ashby & Townsend, 1986;Thomas, 2001aThomas, , 2001b and marginal signal detection parameter comparisons (e.g., Kadlec & Townsend, 1992a;Thomas, 2001b). We turn now to consideration of an apparently thus far undocumented implicational relationship between these tests of separability.…”

Section: Redundancy Power and False Alarms In Tests Of Separabilitymentioning

confidence: 99%

“…It is crucial to test marginal response invariance at both levels on each dimension, and it is very important to construct the test statistics carefully, since the signs of the test statistics provide valuable information about the relative locations of the underlying perceptual distributions. For j 0 1, 2, the test statistic for each level on the A dimension is as follows (Thomas, 2001a):…”

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confidence: 99%

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Decisional separability, model identification, and statistical inference in the general recognition theory framework

Silbert

Thomas

2012

Psychon Bull Rev

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Recent work in the general recognition theory (GRT) framework indicates that there are serious problems with some of the inferential machinery designed to detect perceptual and decisional interactions in multidimensional identification and categorization (Mack, Richler, Gauthier, & Palmeri, 2011). These problems are more extensive than previously recognized, as we show through new analytic and simulation-based results indicating that failure of decisional separability is not identifiable in the Gaussian GRT model with either of two common response selection models. We also describe previously unnoticed formal implicational relationships between seemingly distinct tests of perceptual and decisional interactions. Augmenting these formal results with further simulations, we show that tests based on marginal signal detection parameters produce unacceptably high rates of incorrect statistical significance. We conclude by discussing the scope of the implications of these results, and we offer a brief sketch of a new set of recommendations for testing relationships between dimensions in perception and response selection in the full-factorial identification paradigm.

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Section: Decisional Separability and Model Identification In Gaussianmentioning

confidence: 99%

Section: Redundancy Power and False Alarms In Tests Of Separabilitymentioning

confidence: 99%

mentioning

confidence: 99%

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Decisional separability, model identification, and statistical inference in the general recognition theory framework

Silbert

Thomas

2012

Psychon Bull Rev

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“…Applying GRT to empirical data to uncover perceptual and decisional loci of dimensional interactions has been performed using two main approaches. One approach involves fitting models to observed data that impose parameter constraints that implement particular violations of GRT constructs (e.g., Ashby & Lee, 1991;Macho, 2007;Maddox, 2001;Maddox & Bogdanov, 2000;Thomas, 2001;Wickens, 1992). Analysis and comparison of these models permits inferences about which GRT constructs hold and which are violated for a given task and stimulus set.…”

Section: Dimensional Interactions In General Recognition Theorymentioning

confidence: 99%

“…Are dimensions processed independently or do they interact, and if so, how? This fundamental question has been asked for a broad range of domains, including simple perceptual stimuli (e.g., Shepard, 1964), faces (e.g., Richler et al, 2008;Thomas, 2001;Wenger & Ingvalson, 2002), multimodal perception-action (e.g., Amazeen & DaSilva, 2005) and visual-haptic stimuli (e.g., Oberle & Amazeen, 2003), and social perception (e.g., Farris, Viken, & Treat, 2010).…”

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confidence: 99%