A hierarchical Bayesian approach to distinguishing serial and parallel processing

Journal of Mathematical Psychology

Volumn 79, Issue , 2017, Pages 13-22

  Houpt, Joseph W ^a   Fifić, Mario ^b  

^a WRIGHT STATE UNIVERSITY   (United States)

^b GRAND VALLEY STATE UNIVERSITY   (United States)

Author keywords

Bayesian modeling; Response times; Serial parallel; Systems factorial technology

Indexed keywords

EID: 85019990880     PISSN: 00222496     EISSN: 10960880     Source Type: Journal    
DOI: 10.1016/j.jmp.2017.05.001     Document Type: Article

References (43)

1. Busemeyer, J.R., Diederich, A., Cognitive modeling. 2010, Sage.
2. Dzhafarov, E.N., Selective influence through conditional independence. Psychometrika 68 (2003), 7–26.
3. Dzhafarov, E.N., Kujala, J.V., The joint distribution criterion and the distance tests for selective probabilistic causality. Frontiers in Psychology, 1, 2010.
4. Dzhafarov, E.N., Kujala, J.V., On selective influences, marginal selectivity, and bell/chsh inequalities. Topics in Cognitive Science 6 (2014), 121–128, 10.1111/tops.12060.
5. Dzhafarov, E.N., Schweickert, R., Sung, K., Mental architectures with selectively influenced but stochastically interdependent components. Journal of Mathematical Psychology 48 (2004), 51–64.
6. Eidels, A., Townsend, J.T., Hughes, H.C., Perry, L.A., Evaluating perceptual integration: uniting response-time-and accuracy-based methodologies. Attention, Perception, & Psychophysics 77 (2015), 659–680.
7. Fifić, M., Simple factorial tweezers for detecting delicate serial and parallel processes. Houpt, J.W., Blaha, L.M., (eds.) Mathematical models of perception and cognition: a festschrift for James T. Townsend, Vol. 1, 2016, Psychology Press, New York, 77–106.
8. Harris, J. (2008). Mindmodeling@home: a large-scale computational cognitive modeling infrastructure. In Proceedings of the sixth annual conference on systems engineering research 2008, Los Angeles, CA, USA (pp. 246–252).
9. Heathcote, A., Brown, S., Wagenmakers, E.J., Eidels, A., Distribution-free tests of stochastic dominance for small samples. Journal of Mathematical Psychology 54 (2010), 454–463.
10. Houpt, J.W., Blaha, L.M., McIntire, J.P., Havig, P.R., Townsend, J.T., Systems factorial technology with R. Behavior Research Methods 46 (2013), 307–330.
11. Houpt, J.W., Burns, D.M., Statistical analyses for systems factorial technology. Little, D., Altieri, N., Fifić, M., Yang, C.-T., (eds.) Systems factorial technology: a theory driven methodology for the identification of perceptual and cognitive mechanisms, 2017, Academic Press, Cambridge, MA.
12. Houpt, J.W., & Fifić, M. (2013). A hierarchical approach to distinguishing serial and parallel processing. In Annual meeting of the psychonomic society. Toronto, ON.
13. Houpt, J.W., Heathcote, A., Eidels, A., Bayesian analyses of cognitive architecture. Psychological Methods, 2017.
14. Houpt, J.W., MacEachern, S.N., Peruggia, M., Townsend, J.T., Van Zandt, T., Semiparametric Bayesian approaches to systems factorial technology. Journal of Mathematical Psychology 75 (2016), 68–85, 10.1016/j.jmp.2016.02.008.
15. Houpt, J.W., Townsend, J.T., The statistical properties of the survivor interaction contrast. Journal of Mathematical Psychology 54 (2010), 446–453.
16. Houpt, J.W., Townsend, J.T., Statistical measures for workload capacity analysis. Journal of Mathematical Psychology 56 (2012), 341–355.
17. Houpt, J., Townsend, J., Donkin, C., A new perspective on visual word processing efficiency. Acta Psychologica 145 (2014), 118–127.
18. Johnson, S.A., Blaha, L.M., Houpt, J.W., Townsend, J.T., Systems factorial technology provides new insights on global–local information processing in autism spectrum disorders. Journal of Mathematical Psychology 54 (2010), 53–72.
19. Kirk, R.E., Experimental design: procedures for the behavioral sciences. 4th ed., 2012, Sage, Thousand Oaks, CA.
20. Kruschke, J.K., Doing bayesian data analysis: a tutorial with R and BUGS. 2010, Academic Press, Amsterdam.
21. Mordkoff, J.T., Yantis, S., An interactive race model of divided attention. Journal of Experimental Psychology: Human Perception and Performance 17 (1991), 520–538.
22. Ohio Supercomputer Center (1987). Ohio supercomputer center. http://osc.edu/ark:/19495/f5s1ph73.
23. Ohio Supercomputer Center (2012). Oakley supercomputer. http://osc.edu/ark:/19495/hpc0cvqn.
24. R Development Core Team (2011). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing Vienna, Austria. URL: http://www.R-project.org ISBN 3-900051-07-0.
25. Rouder, J.N., Morey, R.D., Speckman, P.L., Province, J.M., Bayes factors for ANOVA designs. Journal of Mathematical Psychology 56 (2012), 356–374.
26. Schreiber, B.T., Stock, W.A., Bennett, W. Jr., Distributed Mission Operations Within-Simulator Training Effectiveness Baseline Study: Metric Development and Objectively Quantifying the Degree of Learning. Technical Report., 2006, Air Force Research Laboratory, Mesa, AZ URL: http://www.dtic.mil/dtic/tr/fulltext/u2/a461867.pdf.
27. Schweickert, R., Giorgini, M., Dzhafarov, E., Selective influence and response time cumulative distribution functions in serial-parallel task networks. Journal of Mathematical Psychology 44 (2000), 504–535.
28. Stan Development Team (2014). Stan: A C++ library for probability and sampling, version 2.5.0. URL: http://mc-stan.org/.
29. Stan Development Team (2015). Stan Modeling Language Users Guide and Reference Manual, Version 2.9.0. URL: http://mc-stan.org/.
30. Thiele, J. (2014). Bayesian modeling in systems factorial technology. In Annual meeting of the psychonomic society. Long Beach, CA.
31. Thiele, J.E., & Rouder, J.N. (2016). Bayesian analysis for systems factorial technology. URL: http://pcl.missouri.edu/sites/default/files/p_8.pdf.
32. Townsend, J.T., A note on the identifiability of parallel and serial processes. Perception & Psychophysics 10 (1971), 161–163.
33. Townsend, J.T., Some results concerning the identifiability of parallel and serial processes. The British Journal of Mathematical and Statistical Psychology 25 (1972), 168–199.
34. Townsend, J.T., Ashby, F.G., The stochastic modeling of elementary psychological processes. 1983, Cambridge University Press, Cambridge.
35. Townsend, J.T., Fifić, M., Parallel and serial processing and individual differences in high-speed scanning in human memory. Perception & Psychophysics 66 (2004), 953–962.
36. Townsend, J.T., Nozawa, G., Spatio-temporal properties of elementary perception: An investigation of parallel, serial and coactive theories. Journal of Mathematical Psychology 39 (1995), 321–360.
37. Townsend, J.T., Thomas, R.D., Stochastic dependencies in parallel and serial models: Effects on systems factorial interactions. Journal of Mathematical Psychology 38 (1994), 1–24.
38. Van Zandt, T., Analysis of response time distributions. Wixted, J.T., Pashler, H., (eds.) Stevens’ handbook of experimental psychology, Vol. 4, 3rd ed., 2002, Wiley Press, New York, 461–516.
39. Yang, C.-T., Chang, T.-Y., Wu, C.-J., Relative change probability affects the decision process of detecting multiple feature changes. Journal of Experimental Psychology: Human Perception and Performance, 2012 Advance online publication.
40. Yang, H., Fifić, M., Townsend, J.T., Survivor interaction contrast wiggle predictions of parallel and serial models for an arbitrary number of processes. Journal of Mathematical Psychology 58 (2014), 21–32, 10.1016/j.jmp.2013.12.001 URL: http://www.sciencedirect.com/science/article/pii/S0022249613001223.
41. Yang, C.-T., Hsu, Y.-F., Huang, H.-Y., Yeh, Y.-Y., Relative salience affects the process of detecting changes in orientation and luminance. Acta Psychologica 138 (2011), 377–389.
42. Yang, C.-T., Little, D.R., Hsu, C.-C., The influence of cueing on attentional focus in perceptual decision making. Attention, Perception, & Psychophysics 76 (2014), 2256–2275.
43. Zhang, R., Dzhafarov, E.N., Noncontextuality with marginal selectivity in reconstructing mental architectures. Frontiers in Psychology, 6, 2015.