Diffusion Model Analysis with fast-dm
This web page is the home of fast-dm, a programm for fast parameter estimation of Ratcliff's (1978) diffusion model. The algorithm is described in the articles "A Fast Numerical Algorithm for the Estimation of Diffusion-Model Parameters" (Voss & Voss, 2008) and "Fast-dm: A Free Program for Efficient Diffusion Model Analysis" (Voss & Voss, 2007). The programm was written by Jochen Voss and Andreas Voss.
With a Diffusion Model data analysis, it is possible to analyse data from any fast binary decision task. A diffusion-model data analysis is based on the distributions of both correct and erroneous responses. From these distributions a set of parameters is estimated that allows to draw conclusions about the underlying cognitive processes (Voss, Rothermund, & Voss, 2004).
Downloads
Fast-dm is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License. See the file COPYING in the source code archives for details.
Below is the fast-dm source for download. We offer ".tar.gz" and ".zip" archives (the contents of both are identical). Some installation instructions can be found in the file README.
fast-dm-29
Release 29 fixes jet another minor bug.
Source
- fast-dm-29.tar.gz (128kb)
- fast-dm-28.zip (237kb)
Microsoft Windows Binaries
- fast-dm-29-win32.zip (93kb)
fast-dm-28
Release 28 fixes a bug introduced in fast-dm release 27. As a nice side-effect the program is now faster for some parameter settings.
Source
- fast-dm-28.tar.gz (127kb)
- fast-dm-28.zip (143kb)
Microsoft Windows Binaries
- fast-dm-28-win32.zip (93kb)
fast-dm-26
Source
- fast-dm-26.tar.gz (126kb)
- fast-dm-26.zip (149kb)
Microsoft Windows Binaries
- fast-dm-26-win32.zip (103kb, signature fast-dm-26-win32.zip.sig)
References
Please note that some of the texts available here are protected by a password. In this case VOSS will help you!
- Voss, A., Voss, J., & Klauer, K.C. (2010). Separating response tendency and decision biases: Arguments for an additional parameter in Ratcliff?s diffusion model.British Journal of Mathematical and Statistical Psychology, 63, 539-555. [pdf]
- Voss, A. (2009). The Analysis of Cognitive Processes with Stochastic Diffusion Models. Habilitationsschrift. Universität Freiburg. [pdf]
- Spaniol, J., Voss, A., & Grady, C.L. (2008). Aging and Emotional Memory: Cognitive Mechanisms Underlying the Positivity Effect. Psychology and Aging, 23, 859-872. [pdf]
- Voss, A., Rothermund, K. & Brandtstädter, J. (2008). Interpreting Ambiguous Stimuli: Separating Perceptual and Judgmental Biases. Journal of Experimental Social Psycholgy, 2008, 44, 1048-1056. [pdf]
- Voss, A., & Voss, J. (2008). A Fast Numerical Algorithm for the Estimation of Diffusion-Model Parameters. Journal of Mathematical Psychology, 52, 1-9. [pdf]
- Klauer, K.C., Voss, A., Schmitz, F., & Teige-Mocigemba, S. (2007). Process Components of the Implicit Association Test: A Diffusion-Model Analysis. Journal of Personality and Social Psychology, 93, 353-368. [pdf]
- Voss, A., & Voss, J. (2007). Fast-dm: A Free Program for Efficient Diffusion Model Analysis. Behavioral Research Methods, 39, 767-775. [pdf]
- Spaniol, J., Madden, D.J., & Voss, A. (2006). A diffusion model analysis of adult age differences in episodic and semantic long-term memory retrieval. Journal of Experimental Psychology: Learning, Memory & Cognition, 32, 101-117. [pdf]
- Voss, A., Rothermund, K., & Voss, J. (2004). Interpreting the parameters of the diffusion model: An empirical validation. Memory and Cognition, 32, 1206-1220. [pdf]
