Empirical Recovery of Response Time Decomposition Rules II. Discriminability of Serial and Parallel Architectures

Cortese, James M.; Dzhafarov, Ehtibar N.

doi:10.1006/jmps.1996.0021

Cited by 10 publications

(7 citation statements)

References 15 publications

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“…In this case the proportion of variance contributed by base time, and the impact of base time on our model selection tools, would remain small. We eagerly anticipate the marriage of theoretical approaches such as Fourier deconvolution (Goldstone, 2000, but note Sheu andRatcliff (1995)) and formal nonparametric tests (Cortese and Dzhafarov, 1996;Van Zandt, 2002) with novel neuroimaging techniques toward an understanding and resolution of the base time problem.…”

Section: Varying Views Of Base Timementioning

confidence: 99%

Consequences of base time for redundant signals experiments

Townsend

Honey

2007

Journal of Mathematical Psychology

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We report analytical and computational investigations into the effects of base time on the diagnosticity of two popular theoretical tools in the redundant signals literature: (1) the race model inequality and (2) the capacity coefficient. We show analytically and without distributional assumptions that the presence of base time decreases the sensitivity of both of these measures to model violations. We further use simulations to investigate the statistical power model selection tools based on the race model inequality, both with and without base time. Base time decreases statistical power, and biases the race model test toward conservatism. The magnitude of this biasing effect increases as we increase the proportion of total reaction time variance contributed by base time. We marshal empirical evidence to suggest that the proportion of reaction time variance contributed by base time is relatively small, and that the effects of base time on the diagnosticity of our modelselection tools are therefore likely to be minor. However, uncertainty remains concerning the magnitude and even the definition of base time. Experimentalists should continue to be alert to situations in which base time may contribute a large proportion of the total reaction time variance.

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Section: Varying Views Of Base Timementioning

confidence: 99%

Consequences of base time for redundant signals experiments

Townsend

Honey

2007

Journal of Mathematical Psychology

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“…For a critical analysis, see Van Zandt and Ratcliff (1995). A generalization of this technique is presented in Dzhafarov and Schweickert (1995), Dzhafarov and Cortese (1996), and Cortese and Dzhafarov (1996). With the generalization one can test not only for the operation of addition, but for virtually any operation that is commutative and associative.…”

Section: Figmentioning

confidence: 99%

Selective Influence and Response Time Cumulative Distribution Functions in Serial-Parallel Task Networks

Schweickert¹,

Giorgini²,

Dzhafarov³

2000

Journal of Mathematical Psychology

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“…In the completely analogous discussion of unconditionally selective influences this situation is considered in Cortese and Dzhafarov (1996), Dzhafarov (1997). In our case, the unobservable components [X 1 , X 2 ] of X can be defined as those conditionally selectively influenced by [* 1 , * 2 , * 3 ] as shown in Fig.…”

Section: 2mentioning

confidence: 95%

“…These extreme special cases of stochastic in(ter)dependence under selective influence are analyzed in Dzhafarov and Schweickert (1995), Cortese and Dzhafarov (1996) and Dzhafarov and Cortese (1996).…”

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confidence: 99%

Conditionally Selective Dependence of Random Variables on External Factors

Dzhafarov

1999

Journal of Mathematical Psychology

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Selective influence of experimental factors upon observable or hypothetical random variables is a key concept in the analysis of processing architectures and response time decompositions. This paper deals with the notion of conditionally selective influence, defined as follows. Let {X1, em leader, Xn} be stochastically interdependent random variables (e.g., hypothetical components of response time), and let Phi be a set of external factors affecting the joint distribution of {X1, em leader, Xn}. A subset of factors &Lambdai conditionally selectively influences Xi if at any fixed values of the remaining random variables the conditional distribution of Xi only depends on factors inside &Lambdai. The notion of conditional selectivity generalizes the relationship between factors and random variables described in Townsend (1984) as "indirect nonselectivity." This paper establishes the structure of the joint distribution of {X1, em leader, Xn} that is necessary and sufficient for {X1, em leader, Xn} to be conditionally selectively influenced by (not necessarily disjoint) factor subsets {&Lambda1, em leader, Gamman}, respectively. The notion of conditional selectivity is compared to that of unconditional selectivity, defined as follows. A subset of factors &Gammai unconditionally selectively influences Xi if the latter can be presented as a deterministic function of &Gammai and of some random variables (the same for all Xi, i=1, em leader, n) whose joint distribution does not depend on any factors from Phi. The two forms of selective influence are generally incompatible. Copyright 1999 Academic Press.

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Empirical Recovery of Response Time Decomposition Rules II. Discriminability of Serial and Parallel Architectures

Cited by 10 publications

References 15 publications

Consequences of base time for redundant signals experiments

Consequences of base time for redundant signals experiments

Selective Influence and Response Time Cumulative Distribution Functions in Serial-Parallel Task Networks

Conditionally Selective Dependence of Random Variables on External Factors

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