Reference health
Applying Occam’s razor in modeling cognition: A Bayesian approach
4 of 56 checkable references need attention · checked 2026-08-29
At the dated check, the references listed below either did not resolve in Crossref or DataCite, or carried a retraction notice. Each one is shown with the registry record that put it there.
23 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
References needing attention
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The 52 checked references that resolve
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A note on measurement of contingency between two binary variables in judgment tasks
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Decision rules in the perception and categorization of multidimensional stimuli.
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Model Selection and Akaike's Information Criterion (AIC): The General Theory and its Analytical Extensions
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Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment.
resolves10.1111/j.2517-6161.1995.tb02042.x
Bayesian Model Choice Via Markov Chain Monte Carlo Methods
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Comparing strong and weak models by fitting them to computer-generated data
resolves10.1037/0033-2909.109.3.512
Model selection in covariance structures analysis and the "problem" of sample size: A clarification.
resolves10.1037/0096-3445.121.3.364
Selectivity, scope, and simplicity of models: A lesson from fitting judgments of perceived depth.
resolves10.1109/TPAMI.1984.4767596
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
resolves10.1086/171844
A new method for the detection of a periodic signal of unknown shape and period
resolves10.1093/biomet/57.1.97
Monte Carlo sampling methods using Markov chains and their applications
resolves10.1037/0096-1523.20.6.1311
Models of visual word recognition: Sampling the state of the art.
resolves10.1037/0033-295X.99.1.22
ALCOVE: An exemplar-based connectionist model of category learning.
resolves10.2307/2291388
Robust Bayesian Model Selection for Autoregressive Processes With Additive Outliers
resolves10.1037/0096-3445.122.1.115
The paradigm and the fuzzy logical model of perception are alive and well.
resolves10.1037/0033-295X.89.6.609
A theory for the storage and retrieval of item and associative information.
resolves10.1037/0096-3445.115.1.39
Attention, similarity, and the identification–categorization relationship.
resolves10.1111/j.2517-6161.1993.tb01466.x
Bayesian Computation Via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods
resolves10.1207/s15327906mbr2502_4
Structural Model Evaluation and Modification: An Interval Estimation Approach
resolves10.3758/BF03214411
Statistical mimicking of reaction time data: Single-process models, parameter variability, and mixtures
resolves10.2307/2986121
Bayesian Analysis of Linear and Non-Linear Population Models by Using the Gibbs Sampler
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no DOI — not checkedAkaike, H. (1973). Information theory and an extension of the maximum likelihood principle. In B. N. Petrox & F. Caski (Eds.),Second International Symposium on Information Theory (p. 267). Budapest: Akademiai Kiado.
no DOI — not checkedAkaike, H. (1983). Information measures and model selection.Bulletin of the International Statistical Institute,50, 277–290.
no DOI — not checkedAnderson, J. R. (1990).The adaptive character of thought. Hillsdale, NJ: Erlbaum.
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no DOI — not checkedAshby, F. G. (1992). Multidimensional models of categorization. In F. G. Ashby (Ed.),Multidimensional models of perception and cognition (pp. 449–483). Hillsdale, NJ: Erlbaum.
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no DOI — not checkedJeffreys, H. (1961).Theory of probability (3rd ed.). New York: Oxford University Press.
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no DOI — not checkedRaftery, A. E. (1993). Bayesian model selection in structural equation models. In K. A. Bollen & J. S. Long (Eds.),Testing structural equation models (pp. 163–180). Thousand Oaks, CA: Sage.
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no DOI — not checkedRissanen, J. (1990). Complexity of models. In W. H. Zurek (Ed.),Complexity, entropy, and the physics of information (pp. 117–125). Reading, MA: Addison-Wesley.
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no DOI — not checkedTakane, Y., &Shibayama, T. (1992). Structure in stimulus identification data. In F. G. Ashby (Ed.),Multidimensional models of perception and cognition (pp. 335–362). Hillsdale, NJ: Erlbaum.
no DOI — not checkedThisted, R. A. (1988).Elements of statistical computing: Numerical computation. New York: Chapman & Hall.
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