A hierarchical Bayesian approach to distinguishing serial and parallel processing

DOI10.1016/j.jmp.2017.05.001zbMath1396.91665OpenAlexW2621248911MaRDI QIDQ1679030

Joseph W. Houpt, Mario Fific

Publication date: 8 November 2017

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://works.bepress.com/joseph_houpt/47

zbMATH Keywords

response timesBayesian modelingserial-parallelsystems factorial technology

Mathematics Subject Classification ID

Bayesian inference (62F15) Cognitive psychology (91E10) Measurement and performance in psychology (91E45) Applications of statistics to psychology (62P15)

Related Items (7)

Systems factorial technology analysis of mixtures of processing architectures ⋮ Parametric supplements to systems factorial analysis: identifying interactive parallel processing using systems of accumulators ⋮ Comparative estimation systems perform under severely limited workload capacity ⋮ Hierarchical Bayesian mixture models of processing architectures and stopping rules ⋮ The balance between vision and touch ⋮ Adaptive design for systems factorial technology experiments ⋮ Is there variation across individuals in processing? Bayesian analysis for systems factorial technology

Uses Software

• R
• BUGS
• Stan

Cites Work

• Unnamed Item
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• Systems factorial technology provides new insights on global-local information processing in autism spectrum disorders
• Stochastic dependencies in parallel and serial models: Effects on systems factorial interactions
• Mental architectures with selectively influenced but stochastically interdependent components.
• Selective influence and response time cumulative distribution functions in serial-parallel task networks.
• Spatio-temporal properties of elementary perception: an investigation of parallel, serial, and coactive theories
• Selective influence through conditional independence
• Statistical measures for workload capacity analysis
• SOME RESULTS CONCERNING THE IDENTIFIABILITY OF PARALLEL AND SERIAL PROCESSES

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