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Research Article

Are the Bayesian Information Criterion (BIC) and the Akaike Information Criterion (AIC) Applicable in Determining the Optimal Fit and Simplicity of Mechanistic Models?

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References

  • Akaike, H. 1974. “A New Look at the Statistical Model Identification.” IEEE Transactions on Automatic Control 19: 716–723. https://doi.org/10.1109/TAC.1974.1100705
  • Bandyopadhayay, P. S., R. J. Boik, and P. Prasun Basu. 1996. “The Curve Fitting Problem: A Bayesian Approach.” Philosophy of Science 63: S264–S272. https://doi.org/10.1086/289960
  • Bandyopadhyay, P. S., J. G. Bennett, and M. D. Higgs. 2015. “How to Undermine Underdetermination?” Foundations of Science 20: 107–127. https://doi.org/10.1007/s10699-014-9353-3
  • Bandyopadhyay, P. S., and R. J. Boik. 1999. “The Curve Fitting Problem: a Bayesian Rejoinder.” Philosophy of Science 66: S390–S402. https://doi.org/10.1086/392740
  • Baumgartner, M. 2008. “Regularity Theories Reassessed.” Philosophia 36: 327–354. https://doi.org/10.1007/s11406-007-9114-4
  • Baumgartner, M., and C. Falk. 2023. “Boolean Difference-making: a Modern Regularity Theory of Causation.” The British Journal for the Philosophy of Science 74: 171–197.
  • Bechtel, W., and A. Abrahamsen. 2005. “Explanation: A Mechanist Alternative.” Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 36: 421–441. https://doi.org/10.1016/j.shpsc.2005.03.010
  • Bechtel, W., and R. C. Richardson. 1993. Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research. New York: Princeton University Press.
  • Box, G. E. P. 1976. “Science and Statistics.” Journal of the American Statistical Association 71: 791–799. https://doi.org/10.1080/01621459.1976.10480949
  • Burnham, K. P., and D. R. Anderson. 2002. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd ed. New York: Springer.
  • Burnham, K. P., and D. R. Anderson. 2004. “Multimodel Inference: Understanding AIC and BIC in Model Selection.” Sociological Methods & Research 33: 261–304. https://doi.org/10.1177/0049124104268644
  • Chakrabarti, A., and J. K. Ghosh. 2011. “AIC, BIC and Recent Advances in Model Selection.” In Handbook of the Philosophy of Science: Vol. 7. Philosophy of Statistics, edited by P. S. Bandyopadhyay, and M. R. Forster, 583–605. Amsterdam, The Netherlands: Elsevier.
  • Chirimuuta, M. 2014. “Minimal Models and Canonical Neural Computations: The Distinctness of Computational Explanation in Neuroscience.” Synthese 191: 127–153. https://doi.org/10.1007/s11229-013-0369-y
  • Claeskens, G., and N. L. Hjort. 2008. Model Selection and Model Averaging. Cambridge: Cambridge University Press.
  • Couch, M. B. 2011. “Mechanisms and Constitutive Relevance.” Synthese 183: 375–388. https://doi.org/10.1007/s11229-011-9882-z
  • Craver, C. 2001. “Role Functions, Mechanisms, and Hierarchy.” Philosophy of Science 68: 53–74. https://doi.org/10.1086/392866
  • Craver, C. 2007. Explaining the Brain. New York: Oxford University Press.
  • Craver, C. 2008. “Constitutive Explanatory Relevance.” Journal of Philosophical Research 32: 3–20. https://doi.org/10.5840/jpr20073241
  • Craver, C. 2009. “Mechanisms and Natural Kinds.” Philosophical Psychology 22: 575–594. https://doi.org/10.1080/09515080903238930
  • Craver, C. F., and A. Alexandrova. 2008. “No Revolution Necessary: Neural Mechanisms for Economics.” Economics & Philosophy 24: 381–406. https://doi.org/10.1017/S0266267108002034
  • Craver, C., and L. Darden. 2001. “Discovering Mechanisms in Neurobiology.” In Theory and Method in the Neurosciences, edited by P. Machamer, R. Grush, and P. McLaughlin, 112–137. Pittsburgh: University of Pittsburgh Press.
  • Craver, C., and J. Tabery. 2023. “Mechanisms in Science.” In The Stanford Encyclopedia of Philosophy (Fall 2023 Edition), edited by Edward N. Zalta, and Uri Nodelman. Metaphysics Research Lab, Stanford University. https://plato.stanford.edu/archives/fall2023/entries/science-mechanisms.
  • Dennis, B., J. M. Ponciano, M. L. Taper, and S. R. Lele. 2019. “Errors in Statistical Inference under Model Misspecification: Evidence, Hypothesis Testing, and AIC.” Frontiers in Ecology and Evolution 7: 372. https://doi.org/10.3389/fevo.2019.00372
  • Fazekas, P., and G. Kertész. 2011. “Causation at Different Levels: Tracking the Commitments of Mechanistic Explanations.” Biology & Philosophy 26: 365–383. https://doi.org/10.1007/s10539-011-9247-5
  • Fisher, R. A. 1922. “On the Mathematical Foundations of Theoretical Statistics.” Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character 222: 309–368.
  • Forster, M. R. 1999. “Model Selection in Science: The Problem of Language Variance.” The British Journal for the Philosophy of Science 50: 83–102. https://doi.org/10.1093/bjps/50.1.83
  • Forster, M. R. 2001. “The New Science of Simplicity.” In Simplicity, Inference and Modelling: Keeping It Sophisticatedly Simple, edited by A. Zellner, H. A. Keuzenkamp, and M. McAleer, 83–119. Cambridge: Cambridge University Press.
  • Forster, M. R., G. Raskutti, R. Stern, and N. Weinberger. 2018. “The Frugal Inference of Causal Relations.” The British Journal for the Philosophy of Science 69: 821–848. https://doi.org/10.1093/bjps/axw033
  • Forster, M., and E. Sober. 1994. “How to Tell when Simpler, More Unified, or Less Ad Hoc Theories Will Provide More Accurate Predictions.” The British Journal for the Philosophy of Science 45: 1–35. https://doi.org/10.1093/bjps/45.1.1
  • Gebharter, A. 2017. Causal Nets, Interventionism, and Mechanisms: Philosophical Foundations and Applications. Synthese Library 381. Dordrecht: Springer.
  • Glennan, S. S. 1996. “Mechanisms and the Nature of Causation.” Erkenntnis 44: 49–71. https://doi.org/10.1007/BF00172853
  • Gluth, S., J. M. Hotaling, and J. Rieskamp. 2017. “The Attraction Effect Modulates Reward Prediction Errors and Intertemporal Choices.” Journal of Neuroscience 37: 371–382. https://doi.org/10.1523/JNEUROSCI.2532-16.2016
  • Harbecke, J. 2010. “Mechanistic Constitution in Neurobiological Explanations.” International Studies in the Philosophy of Science 24: 267–285.
  • Huneman, P. 2010. “Topological Explanations and Robustness in Biological Sciences.” Synthese 177: 213–245. https://doi.org/10.1007/s11229-010-9842-z
  • Machamer, P., L. Darden, and C. F. Craver. 2000. “Thinking about Mechanisms.” Philosophy of science 67 (1): 1–25. https://doi.org/10.1086/392759
  • Mierau, J., J. Harbecke, and S. Schmidt. 2023. Uncovering Constitutive-Mechanistic Models in the Cognitive and Biological Sciences: A Boolean Inferential Method.
  • Morris, R. 1984. “Developments of a Water-Maze Procedure for Studying Spatial Learning in the Rat.” Journal of Neuroscience Methods 11: 47–60. https://doi.org/10.1016/0165-0270(84)90007-4
  • Morris, R. 1989. “Synaptic Plasticity and Learning: Selective Impairment of Learning Rats and Blockade of Long-term Potentiation In Vivo by the n-Methyl-d-Aspartate Receptor Antagonist AP5.” Journal of Neuroscience 9: 3040–3057. https://doi.org/10.1523/JNEUROSCI.09-09-03040.1989
  • Morris, R., E. Anderson, G. Lynch, and M. Baudry. 1986. “Selective Impairment of Learning and Blockade of LTP by an NMDA Receptor Antagonist AP5.” Nature 319: 774–776. https://doi.org/10.1038/319774a0
  • Morris, R., P. Garrud, J. Rawlins, and J. O’Keefe. 1982. “Place Navigation Impaired in Rats with Hippocampal Lesions.” Nature 297: 681–683. https://doi.org/10.1038/297681a0
  • Pearl, J. 2009. Causality: Models, Reasoning, and Inference. Cambridge, UK: Cambridge University Press.
  • Pitt, M. A., and I. J. Myung. 2002. “When a Good Fit Can be Bad.” Trends in cognitive sciences 6: 421–425. https://doi.org/10.1016/S1364-6613(02)01964-2
  • Schupbach, J. N., and J. Sprenger. 2011. “The Logic of Explanatory Power.” Philosophy of Science 78: 105–127. https://doi.org/10.1086/658111
  • Schwarz, G. 1978. “Estimating the Dimension of a Model.” The Annals of Statistics 6: 461–464. https://doi.org/10.1214/aos/1176344136
  • Shipley, B. 2013. “The AIC Model Selection Method Applied to Path Analytic Models Compared Using ad-Separation Test.” Ecology 94: 560–564. https://doi.org/10.1890/12-0976.1
  • Shipley, B., and J. C. Douma. 2020. “Generalized AIC and Chi-squared statistics for Path Models Consistent with Directed Acyclic Graphs.” Ecology 101: e02960. https://doi.org/10.1002/ecy.2960
  • Skipper, R. A. 1999. “Selection and the Extent of Explanatory Unification.” Philosophy of Science 66: S196–S209. https://doi.org/10.1086/392725
  • Sober, E. 1981. “The Principle of Parsimony.” The British Journal for the Philosophy of Science 32: 145–156. https://doi.org/10.1093/bjps/32.2.145
  • Sober, E. 2002. “Instrumentalism, Parsimony, and the Akaike Framework.” Philosophy of Science 69: S112–S123. https://doi.org/10.1086/341839
  • Spirtes, P., C. Glymour, and R. Scheines. 2000. Causation, Prediction, and Search, 2nd Edition. Boston: MIT Press.
  • Taylor, A. M., T. Bus, R. Sprengel, P. H. Seeburg, J. N. P. Rawlins, and D. M. Bannerman. 2014. “Hippocampal NMDA Receptors Are Important for Behavioural Inhibition but not for Encoding Associative Spatial Memories.” Philosophical Transactions of the Royal Society B: Biological Sciences 369: 20130149. https://doi.org/10.1098/rstb.2013.0149
  • Vrieze, S. I. 2012. “Model Selection and Psychological Theory: A Discussion of the Differences Between the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC).” Psychological Methods 17: 228–243. https://doi.org/10.1037/a0027127
  • Zhang, J. 2013. “A Comparison of Three Occam's Razors for Markovian Causal Models.” The British Journal for the Philosophy of Science 64: 423–448. https://doi.org/10.1093/bjps/axs005

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