A statistical model for discriminating between subliminal and near-liminal performance

DOI10.1016/j.jmp.2007.09.007zbMath1134.91583OpenAlexW2059694064MaRDI QIDQ924531

Richard D. Morey, Paul L. Speckman, Jeffrey N. Rouder

Publication date: 16 May 2008

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

Full work available at URL: https://doi.org/10.1016/j.jmp.2007.09.007

zbMATH Keywords

Bayesian statisticshierarchical modelspsychometricsMACpsychophysicsprimingchance performancemass at chanceraschsubliminal

Mathematics Subject Classification ID

Psychophysics and psychophysiology; perception (91E30) Measurement and performance in psychology (91E45)

Related Items

Do items order? The psychology in IRT models ⋮ A Bayesian hierarchical model for the measurement of working memory capacity ⋮ Hierarchical single- and dual-process models of recognition memory ⋮ Hierarchical Bayesian parameter estimation for cumulative prospect theory ⋮ Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task ⋮ Problematic effects of aggregation in \(z\)ROC analysis and a hierarchical modeling solution ⋮ Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ

Cites Work

• Computer methods for sampling from gamma, beta, Poisson and binomial distributions
• Markov chains for exploring posterior distributions. (With discussion)
• A neural timing model of visual threshold
• Sampling-Based Approaches to Calculating Marginal Densities
• Generalised Gibbs sampler and multigrid Monte Carlo for Bayesian computation
• Bayesian Analysis of Binary and Polychotomous Response Data
• Unnamed Item
• Unnamed Item
• Unnamed Item