Emeritus Professor Mike Smithson

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Michael Smithson is an Emeritus Professor in the Research School of Psychology at The Australian National University in Canberra, and received his PhD from the University of Oregon. He is the author of Confidence Intervals (2003), Statistics with Confidence (2000), Ignorance and Uncertainty (1989), and Fuzzy Set Analysis for the Behavioral and Social Sciences (1987), co-author of Fuzzy Set Theory: Applications in the Social Sciences (2006), Generalized Linear Models for Categorical and Limited Dependent Variables (2014), and Generalized Linear Models for Bounded and Limited Quantitative Variables (2019), and co-editor of Uncertainty and Risk: Multidisciplinary Perspectives (2008) and Resolving Social Dilemmas: Dynamic, Structural, and Intergroup Aspects (1999). His other publications include more than 180 refereed journal articles and book chapters. His primary research interests are in judgment and decision making under ignorance and uncertainty, statistical methods for the social sciences, and applications of fuzzy set theory to the social sciences.

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Research interests

Judgment and decision making under uncertainty, statistical methods for the social sciences, and applications of fuzzy set theory to the social sciences.


2020-2022 ARC Discovery Grant (with Dr Yiyun Shou), $100,000 pa: Fake News and Post-Truth Impacts: Responses to Conflictive Uncertainty.

2016-2018 ARC Discovery Grant (with Prof. Evan Kidd and Dr Joanne Arciuli), $120,000 pa: Discovering the sources of individual differences in first language acquisition.

2015-2017 ARC Discovery Grant, $80,000 pa: Judgements and Decisions under Ambiguity and Conflict

2012-2014 ARC Discovery Grant, $60,000 pa: Zero-sum thinking

2011-2020 Consultancy, Union Bank of California, approx. $75000: Analysis and input to capital operational risk models


Room 215, Level 2, Building 39



Smithson, M. (online 2023).  The ROC area under the curve (or mean ridit) as an effect-size.  Psychological Methods. https://doi.org/10.1037/met0000601

Kidd, E., Arciuli, J., Christiansen, M.H., and Smithson, M. (online 2023). The sources and consequences of individual differences in statistical learning for language development. Cognitive Development. https://doi.org/10.1016/j.cogdev.2023.101335

Shou, Y., Farrer, L. M., Gulliver, A., Newman, E., Batterham, P. J., & Smithson, M. (2023). Understanding Australian Government Risk Communication Early in the COVID-19 Pandemic: Sociodemographics, Risk Attitudes and Media Consumption. Journal of Health Communication, 1-10. https://doi.org/10.1080/10810730.2023.2197403

Whitecross, W. M., & Smithson, M. (online 2023). Curiously different: interest-curiosity and deprivation-curiosity have distinct benefits and drawbacks.  Personality and Individual Differences, 213, 112310. https://doi.org/10.1016/j.paid.2023.112310

  • Whitecross, W. M., & Smithson, M. (online 2023). Open or opposed to unknowns: How do curious people think and feel about uncertainty?. Personality and Individual Differences, 209, 112210. https://doi.org/10.1016/j.paid.2023.112210

  • Smithson, M. & Shou, Y. (online 2023). Flexible cdf-quantile distributions on the closed unit interval, with software and applications.  Communications in Statistics – Theory and Methodshttps://www.tandfonline.com/doi/full/10.1080/03610926.2023.2166352

  • Shou, Y.,  Smithson, M., Gulliver, A.,  Murray, K., Banfield, M., ..., & Batterham, P. (accepted 10/03/2022). Risk tolerance and changes in COVID-related health behaviors: A longitudinal study. Health Psychology.

  • Smithson, M., Shou, Y., Dawel, A., Calear, A.L., Farrer, L., & Cherbuin, N. (2022). The Psychological benefits of an uncertain world: Hope and optimism in the face of existential threat. Frontiers in  Psychology, 13:749093. doi: 10.3389/fpsyg.2022.74909.

  • Smithson, M. & Broomell, S.B. (2022). Compositional Data Analysis Tutorial. Psychological Methods.  https://doi.org/10.1037/met0000464

  • . Dawel, A., Shou, Y., Gulliver, A., Cherbuin, N., Banfield, M., Murray, K., ... & Smithson, M. (2021). Cause or symptom? A longitudinal test of bidirectional relationships between emotion regulation strategies and mental health symptoms. Emotion.

  • Smithson, M. & Shou, Y. (2021). How Big is (Sample) Space? Judgement and Decision Making with Unknown States and Outcomes.  Decision, 8(4), 237-256.

  • Dawel, A., Shou, Y., Smithson, M., Cherbuin, N., Banfield, M., Calear, A. L., ... & McCallum, S. M. (2020). The effect of COVID-19 on mental health and wellbeing in a representative sample of Australian adults. Frontiers in Psychiatry, 11, 1026.

  • Shou, Y., Olney, J., Smithson, M., and Song, F. (2020). Impact of uncertainty and ambiguous outcome phrasing on moral decision-making. PLOS ONE, 15(5):1–20.

  • Kidd, E., Arciuli, J., Christiansen, M.H., Isbilen, E., Revius, K, and Smithson, M. (2020). Measuring children’s auditory statistical learning via serial recall. Journal of Experimental Child Psychology, 200, 104964.

  • Alzaatreh A., Aljarrah M., Smithson M., Shahbaz S.H., Shahbaz M.Q., Famoye F., and Lee C. (2020).Truncated T-X family of distributions with applications to time and cost to start a business. Methodology and Computing in Applied Probability.  doi.org/10.1007/s11009-020-09801-1.

  • Smithson, M. (2020). Uncertainty. In G. Ritzer & C. Rojek (eds.), Wiley Blackwell Encyclopedia of Sociology, 2nd Edition. London: Wiley, pp. , DOI: 10.1002/9781405165518.wbeosu001.pub2.

  • Bammer, G. et al. (2020). Expertise in research integration and implementation for tackling complex problems: when is it needed, where can it be found and how can it be strengthened? Palgrave Communications 6, 5. doi:10.1057/s41599-019-0380-0

  • Smithson, M. & Shou. Y. (2020). Generalized Linear Models for Bounded and Limited Quantitative Variables.  Los Angleles, CA: Sage.

  • Smithson, M. (2019). Imprecise compositional data analysis: Alternative statistical methods. Proceedings of Machine Learning Research, 103, 364-366.

    Smithson, M. (2019). Incompletely known sample spaces: Models and human intuitions. Proceedings of Machine Learning Research, 103, 367-376.

  • Lane, J, Robbins, RA; Rohan, EMF, Crookes, K, Essex, RW, Maddess, T, Sabeti, F, Mazlin, J-L, Irons, J, Gradden, T, Dawel, A, Barnes, N, He, X, Smithson, M, McKone, E (2019). Caricaturing can improve facial expression recognition in low-resolution images and age-related macular degeneration. Journal of Vision, 19(6): 18. doi:10.1167/19.6.18

  • Smithson, M., Priest, D., Shou, Y., & Newell, B.R. (2019). Ambiguity and conflict aversion when uncertainty is in the outcomes. Frontiers in Psychology, 10, 539. doi: 10.3389/fpsyg.2019.00539
  • Shou, Y. & Smithson, M. (2019). cdfquantreg: An R package for CDF-Quantile Regression. Journal of Statistical Software, 88, 1-30.
  • Smithson, M. (2018). Trusted autonomy under uncertainty. In H. A. Abbass, J. B. Scholz, and D. J. Reid (Eds.), Foundations of Trusted Autonomy.  N.Y.: Springer, pp. 185-201.
  • Ben-Haim, Y. & Smithson, M. (2018). Data-based prediction under uncertainty: CDF-quantile distributions and info-gap robustnessJournal of Mathematical Psychology, 18: 11-30. doi: https://doi-org.virtual.anu.edu.au/10.1016/j.jmp.2018.08.006
  • Smithson, M. & Blakey, P. (2018). New distributions for modeling subjective lower and upper probabilities.  International Journal of Approximate Reasoning, 100: 56–68. doi: https://doi-org.virtual.anu.edu.au/10.1016/j.ijar.2018.05.007
  • Brown, R.F., Thorsteinsson, E.B., Smithson, M., Birmingham, C.L., Aljarallah, H., & Nolan, C. (2017). Can body temperature dysregulation explain the co-occurrence between overweight/obesity, sleep impairment, late-night eating, and a sedentary lifestyle? Eating and Weight Disorders. doi:10.1007/s40519-017-0439-0
  • Smithson, M. (2017). New distributions for modeling subjective lower and upper probabilities. Proceedings of Machine Learning Research, 62, 301-312.
  • Smithson, M., Shou, Y., & Wu, Alice (2017). Question word-order influences on covariate effects: Predicting zero-sum beliefs. Behaviormetrika.  doi: 10.1007/s41237-017-0030-z
  • Egozcue, M., Garcıa, L.F., Katsikopoulos, K.V., & Smithson, M. (2017).  Simple models in finance: Evaluating the accuracy rate of the recognition heuristic.  Journal of Risk Model Validation, 11: 1-21.
  • Smithson, M. & Shou, Y. (2017). CDF-quantile distributions for modeling random variables on the unit interval. British Journal of Mathematical and Statistical Psychology. doi: 10.1111/bmsp.12091
  • Bradley, B. & Smithson, M. (2017). Groupness in Preverbal Infants: Proof of Concept. Frontiers in Psychology. doi.org/10.3389/fpsyg.2017.00385
  • Lee, E., Reynolds, K.J., Subasic, E., Bromhead, D., Lin, H., Marinov, V., & Smithson, M. (2017). Development of a dual school climate and school identification measure–Student (SCASIM-St). Contemporary Educational Psychology, 49, 91-106 doi: 10.1016/j.cedpsych.2017.01.003
  • Corke, M., Bell, J., Goodhew, S.C., Smithson, M., & Edwards, M. (2016). Perceived time slows during fleeting fun or fear. Quarterly Journal of Experimental Psychology. doi 10.1080/17470218.2016.1264000.
  • Smithson, M. (2016). Human understandings of probability. In A. Hájek and C. Hitchcock (Eds.), Oxford Handbook of Probability and Philosophy, Oxford: Oxford University Press, pp. 477-496.
  • Smithson, M. & Shou, Y. (2016). Asymmetries in responses to attitude statements:The example of “zero-sum” beliefs. Frontiers in Psychology, 7: 984. doi: 10.3389/fpsyg.2016.00984
  • Shou, Y. & Smithson, M. (2016). Causal reasoning under ambiguity: An illustration of modelling mixture strategies. Journal of Behavioral Decision Making. 
  • Smithson, M. & Shou, Y. (2016). Moderator Effects Differ on Alternative Effect-Size Measures.  Behavioral Research Methods, doi: 10.3758/s13428-016-0735-z
  • Smithson, M. (2016). Chapter 8. Fuzzy sets and fuzzy logic in the human sciences. In C. Kahraman, U. Kaynak, and A. Yazıcı (Eds.), Fuzzy Logic in its 50th Year: New Developments, Directions and Challenges, Singapore: Springer, pp. 175-186.
  • Shou, Y. & Smithson, M.  (2015). cdfquantreg: Quantile Regression for Random Variables on the Unit Interval. R package version 1.0.
  • Shou, Y. & Smithson, M. (2015) Adapting to an uncertain world: Cognitive capacity and causal reasoning with ambiguous observations. PLoS ONE 10(10): e0140608. doi: 10.1371/journal.pone.0140608.
  • Pushkarskaya, H., Smithson, M., Joseph, J.E., Corbly, C., & Levy, I. (2015) Neural correlates of decision-making under ambiguity and conflict. Frontiers in Behavioral Neuroscience, 9, 325.  doi: 10.3389/fnbeh.2015.00325.
  • Smithson, M., Sopena, A. & Platow, M. (2015) When is group membership zero-sum? Effects of ethnicity, threat, and social identity on dual national identity,  PLOS ONE 1-18, doi: 10.1371/journal.pone.0130539.
  • Smithson, M. & Pushkarskaya, H. (2015) Ignorance and the brain: Are there distinct kinds of unknowns?  In L. McGoey and M. Gross (Eds.), International Handbook of Ignorance Studies, London: Routledge, pp. 114-124. 
  • Smithson, M. (2015) Ignorance studies: Interdisciplinary, multidisciplinary, and transdisciplinary.  In L. McGoey and M. Gross (Eds.), International Handbook of Ignorance Studies, London: Routledge, pp. 385-399. 
  • Smithson, M. (2015) Probability judgments under ambiguity and conflict. Frontiers in Psychology: Quantitative Psychology and Measurement, 6, 1-9, doi: =10.3389/fpsyg.2015.00674.
  • Smithson, M. & Ben-Haim, Y. (2015) Reasoned decision making without math? Adaptability and robustness in response to surprise. Risk Analysis, 35, 1911-1918. doi: 10.1111/risa.12397.
  • Shou, Y. & Smithson. M. (2015) Effects of question formats on causal judgments and model evaluation. Frontiers in Psychology: Quantitative Psychology and Measurement, 6, 1-12, doi: 10.3389/fpsyg.2015.00467.
  • Lewandowsky, S., Oreskes, N., Risbey, J.S., Newell, B.R., & Smithson, M. (2015). Seepage: Climate change denial and its effect on the scientific community. Global Environmental Change, 33, 1-13.
  • Shou, Y. & Smithson, M. (2015). Evaluating predictors of dispersion: A comparison of Dominance Analysis and Bayesian Model Averaging. Psychometrika, 80, 236-256.
  • Platow, M. J., Grace, D. M., & Smithson, M. J. (2014). When immigrants and converts are not truly one of us: Examining the social psychology of marginalizing racism. In K. Rubenstein, F. Jenkins, & M. Nolan (Eds.), Allegiance and Identity in a Globalised World. Cambridge: Cambridge Univesity Press, pp. 192-220.
  • Smithson, M. & Shou, Y. (2014). Randomly stopped sums: Models and psychological applications. Frontiers in Psychology: Quantitative Psychology and Measurement, 1-11, doi: 10.3389/fpsyg.2014.01279
  • Budescu, D.V., Por, H-H., Broomell, S.B., & Smithson, M. (2014) The Interpretation of IPCC Probabilistic Statements around the World. Nature Climate Change. doi: 10.1038/NCLIMATE2194
  • Lewandowsky, S., Risbey, J.S., Smithson, M., Newell, B.R., & Hunter, J. (2014) Scientific Uncertainty and Climate Change: Part I. Uncertainty and Unabated Emissions. Climatic Change, 124, 21-37.
  • Lewandowsky, S., Risbey, J.S., Smithson, M., & Newell, B.R. (2014) Scientific Uncertainty and Climate Change: Part II. Uncertainty and Mitigation. Climatic Change, 124, 39-52.
  • Smithson, M. (2014) Elicitation. In T. Augustin, F. Coolen, G. de Cooman and M. Troffaes (Eds.), An Introduction to Imprecise Probabilities. London: Wiley, pp. 318-328.
  • Smithson, M. and Merkle, E.C. (2014). Generalized Linear Models for Categorical and Continuous Limited Dependent Variables. Boca Raton, Florida: Chapman and Hall.
  • Smithson, M. (2013) Unknowns in dual use dilemmas. In B. Rappert and M. Selgelid (Eds.) On the Dual uses of Science and Ethics : Principles, Practices, and Prospects, ANU E-Press, pp. 165-184.
  • Smithson, M. (2013). Conflict and ambiguity: Preliminary models and empirical tests. Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications, Compiegne, France, 2-5 July 2013: pp. 303-310.
  • Smithson, M. (2012). A simple statistic for comparing moderation of slopes and correlations. Frontiers in Quantitative Psychology and Measurement, 3, 1-9, DOI=10.3389/fpsyg.2012.00231.
  • Verkuilen, J. and Smithson, M. (2012). Mixed and mixture regression models for continuous bounded responses using the beta distribution.  Journal of Educational and Behavioral Statistics, 37, 82-113.
  • Smithson, M., Budescu, D.V., Broomell, S.B., and Por, H.-H. (2012). Never Say 'not:' Impact of negative wording in probability phrases on imprecise probability judgments. International Journal of Approximate Reasoning, 53, 1262-1270.
  • Hájek, A. and Smithson, M. (2012). Rationality and indeterminate probabilities. Synthese, 187, 33-48.
  • Butcher, P., Bouma, A., Stremmelaar, E.F., Bos, A.F., Smithson, M., &Van Braeckel, K.N.J.A. (2012). Visuospatial perception in children born preterm is doubly disadvantaged. Neuropsychology, 26, 723-734.
  • Smithson, M. (2012) Uncertainty. In V.S. Ramachandran (ed.) Encyclopedia of Human Behavior, 2nd Edition. Oxford: Elsevier, pp. 621-628.
  • Platow, M. J., Grace, D. M., & Smithson, M. J. (2011). Examining the preconditions for psychological group membership: Perceived social interdependence as the outcome of self categorization. Social Psychology and Personality Science, 3, 5-13.
  • Smithson, M., Merkle, E.C. and Verkuilen, J. (2011). Beta regression finite mixture models of polarization and priming. Journal of Educational and Behavioral Statistics, 36, 804-831.
  • Smithson, M., Davies, M., & Aimola-Davies, A. (2011). Exploiting test structure: Case series, case-control comparison, and dissociation. Cognitive Neuropsychology, 28(1), 44-64.
  • Merkle, E.C., Smithson, M. and Verkuilen, J. (2011). Using beta-distributed hierarchical models to examine simple mechanisms underlying confidence in decision making.  Journal of Mathematical Psychology, 55, 57-67.
  • Smithson, M., Budescu, D.V., Broomell, S.B., and Por, H.-H. (2011). Never Say 'Not:' Impact of Negative Wording in Probability Phrases on Imprecise Probability Judgments. Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications, Innsbruck, Austria, 25-28 July 2011: pp. 327-333.
  • Smithson, M. (2011) Confidence interval. In M. Lovric (Ed.) International encyclopedia of statistical sciences, Part 3. N.Y.: Springer, 283-284. 
  • Pushkarskaya, H., Liu, X., Smithson, M. and Joseph, J.E. (2010). Beyond risk and ambiguity: deciding under ignorance. Cognitive, Affective, and Behavioral Neuroscience, 10 (3), 382-391.
  • Smithson, M. (2010) When less is more in the recognition heuristic. Judgment and Decision Making, 5, 230-243.
  • Smithson, M. (2010) Ignorance and uncertainty. In V. A. Brown, J. Russell, and J. Harris (Eds). Tackling wicked problems through the transdisciplinary imagination. London: Earthscan, 84-97.
  • Pushkarskaya, H., Smithson, M., Liu, X. and Joseph, J.E. (2010). Neuroeconomics of environmental uncertainty and the theory of firm. In M. Day, A. Stanton, and I. Welpe (Eds.) Neuroeconomics and the Firm. Cheltenham UK: Elgar, 13-28.
  • Smithson, M. (2010) Understanding uncertainty. In G. Bammer (Ed.), Dealing with Uncertainties in Policing Serious Crime. Canberra: ANU E-Press, 27-48.
  • Smithson, M. (2009) How many alternatives? Partitions pose problems for predictions and diagnoses. Social Epistemology, 23, 347-360.
  • Smithson, M. & Segale, C. (2009) Partition priming in judgments of imprecise probabilities. Journal of Statistical Theory and Practice ,3, 169-182.
  • Aimola-Davies, A., Davies, M., Ogden, J., Smithson, M. & White, R.C. (2009).  Cognitive and motivational factors in anosognosia. In T. Bayne & J. Fernandez (Eds.), Delusions and Self-Deception: Affective and Motivational Influences on Belief-Formation. Hove, East Sussex: Psychology Press, 187-225.
  • Selected Older Publications

  • Bammer, G. and Smithson, M. (Eds.) (2008). Uncertainty and Risk: Multidisciplinary Perspectives. London: Earthscan.
  • Smithson, M. and Verkuilen, J. (2006). Fuzzy Set Theory: Applications in the Social Sciences. Quantitative Applications in the Social Sciences Series. Belmont, CA: Sage.
  • Smithson, M. (2003). Confidence intervals. Quantitative Applications in the Social Sciences Series, No. 140. Belmont, CA: Sage.
  • Smithson, M. (1989) Ignorance and uncertainty: Emerging paradigms. New York, NY: Springer.