A hierarchical bayesian statistical framework for response time distributions

By Jeffrey N. Rouder, Dongchu Sun, Paul L. Speckman, Jun Lu, Duo Zhou. 2003

155 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Food Science

View Paper: https://www.semanticscholar.org/paper/5907bf4d7270a7e66293f51e4057246a6d9c7b52

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Denis Cousineau
2. Jeffrey N. Rouder
3. Eric-Jan Wagenmakers
4. Karl Christoph Klauer
5. L. DeCarlo
6. Richard D. Morey
7. Paul L. Speckman
8. Colin J. Davis

In Food Science

1. Denis Cousineau
2. Jeffrey N. Rouder

Citations in the corpus

• A hierarchical framework for modeling speed and accuracy on test items (2007, background): “Rouder et al. (2003) explain why psychological processes with a sensory and problem solving component may fit a Weibull distribution.”
• An introduction to Bayesian hierarchical models with an application in the theory of signal detection (2005, methodology): “We advocate Bayesian hierarchical models for this purpose (Rouder, Lu, Speckman, Sun, & Jiang, 2005; Rouder, Sun, Speckman, Lu, & Zhou, 2003 ).”
• Fitting the three-parameter weibull distribution: review and evaluation of existing and new methods (2009, methodology): “Finally, Bayesian estimation techniques and prior-informed MLE are generalizations of the regular MLE method [22], [23].”