J. F. Ackermann and M. S. Landy, Suboptimal decision criteria are predicted by subjectively weighted probabilities and rewards. Attention, Perception, Psychophysics, vol.77, issue.2, pp.638-658, 2015.
DOI : 10.3758/s13414-014-0779-z
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4336614/pdf

M. D. Alicke, T. L. Davis, and M. V. Pezzo, A Posteriori Adjustment of a Priori Decision Criteria, Social Cognition, vol.12, issue.4, p.281, 1994.
DOI : 10.1521/soco.1994.12.4.281

S. Andersen, G. W. Harrison, M. I. Lau, R. , and E. E. , Eliciting Risk and Time Preferences, Econometrica, vol.76, issue.3, pp.583-618, 2008.
DOI : 10.1111/j.1468-0262.2008.00848.x

F. Balci, P. Simen, R. Niyogi, A. Saxe, J. A. Hughes et al., Acquisition of decision making criteria: reward rate ultimately beats accuracy, Attention, Perception, & Psychophysics, vol.54, issue.10, 2011.
DOI : 10.1016/j.jmp.2009.12.004
URL : https://link.springer.com/content/pdf/10.3758%2Fs13414-010-0049-7.pdf

R. Barkan, D. Zohar, and I. Erev, Accidents and decision making under uncertainty: A comparison of four models. Organizational behavior and human decision processes, pp.118-144, 1998.

J. Baron and J. C. Hershey, Outcome bias in decision evaluation., Journal of Personality and Social Psychology, vol.54, issue.4, p.569, 1988.
DOI : 10.1037/0022-3514.54.4.569

R. Bogacz, E. Brown, J. Moehlis, P. Holmes, and J. D. Cohen, The physics of optimal decision making: A formal analysis of models of performance in two-alternative forced-choice tasks., Psychological Review, vol.113, issue.4, p.700, 2006.
DOI : 10.1037/0033-295X.113.4.700

C. J. Bohil and W. T. Maddox, Category discriminability, base-rate, and payoff effects in perceptual categorization, Perception & Psychophysics, vol.101, issue.2, pp.361-376, 2001.
DOI : 10.1037/0033-295X.101.3.490
URL : https://link.springer.com/content/pdf/10.3758%2FBF03194476.pdf

C. J. Bohil and W. T. Maddox, On the generality of optimal versus objective classifier feedback effects on decision criterion learning in perceptual categorization, Memory & Cognition, vol.101, issue.2, 2003.
DOI : 10.1037/0033-295X.101.3.490

D. H. Brainard, The Psychophysics Toolbox, Spatial Vision, vol.10, issue.4, pp.433-436, 1997.
DOI : 10.1163/156856897X00357

G. S. Brown and K. G. White, The optimal correction for estimating extreme discriminability. Behavior research methods, pp.436-449, 2005.
DOI : 10.3758/bf03192712
URL : https://link.springer.com/content/pdf/10.3758%2FBF03192712.pdf

J. R. Busemeyer and I. J. Myung, An adaptive approach to human decision making: Learning theory, decision theory, and human performance., Journal of Experimental Psychology: General, vol.121, issue.2, p.177, 1992.
DOI : 10.1037/0096-3445.121.2.177
URL : http://smash.psych.nyu.edu/courses/spring09/modeling/materials/busemeyermyung.pdf

C. F. Camerer and R. M. Hogarth, The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework, Journal of Risk and Uncertainty, vol.19, issue.1, pp.7-42, 1999.
DOI : 10.1007/978-94-017-1406-8_2

M. Cohen, J. Tallon, and J. Vergnaud, An experimental investigation of imprecision attitude and its relation with risk attitude and impatience, Theory and Decision, vol.21, issue.1???2, pp.81-109, 2011.
DOI : 10.1002/bs.3830210104
URL : https://hal.archives-ouvertes.fr/halshs-00389674

Z. Dai, F. Galeotti, and M. C. Villeval, Cheating in the lab predicts fraud in the field: An experiment in public transportation, Management Science, 2017.

C. Dave, C. C. Eckel, C. A. Johnson, and C. Rojas, Eliciting risk preferences: When is simple better, Journal of Risk and Uncertainty, issue.3, pp.41219-243, 2010.
DOI : 10.1007/s11166-010-9103-z
URL : http://www.umass.edu/resec/faculty/rojas/docs/Risk.pdf

T. Dohmen, A. Falk, D. Huffman, U. Sunde, J. Schupp et al., INDIVIDUAL RISK ATTITUDES: MEASUREMENT, DETERMINANTS, AND BEHAVIORAL CONSEQUENCES, Journal of the European Economic Association, vol.9, issue.3, pp.522-550, 2011.
DOI : 10.1111/j.1542-4774.2011.01015.x
URL : https://academic.oup.com/jeea/article-pdf/9/3/522/10314305/jeea0522.pdf

C. C. Eckel and P. J. Grossman, Forecasting risk attitudes: An experimental study using actual and forecast gamble choices, Journal of Economic Behavior & Organization, vol.68, issue.1, pp.1-17, 2008.
DOI : 10.1016/j.jebo.2008.04.006

C. C. Eckel, P. J. Grossman, C. A. Johnson, A. C. De-oliveira, C. Rojas et al., School environment and risk preferences: Experimental evidence, Journal of Risk and Uncertainty, vol.3, issue.4, pp.45265-292, 2012.
DOI : 10.1177/152483990200300224

S. W. Ell, A. D. Ing, and W. T. Maddox, Criterial noise effects on rule-based category learning: The impact of delayed feedback, Attention, Perception, & Psychophysics, issue.6, pp.711263-1275, 2009.

I. Erev, Signal detection by human observers: A cutoff reinforcement learning model of categorization decisions under uncertainty., Psychological Review, vol.105, issue.2, p.280, 1998.
DOI : 10.1037/0033-295X.105.2.280

E. Galanter and G. L. Holman, Some invariances of the isosensitivity function and their implications for the utility function of money., Journal of Experimental Psychology, vol.73, issue.3, p.73333, 1967.
DOI : 10.1037/h0024275

F. Gino, L. L. Shu, and M. H. Bazerman, Nameless+harmless=blameless: When seemingly irrelevant factors influence judgment of (un)ethical behavior, Organizational Behavior and Human Decision Processes, vol.111, issue.2, pp.93-101, 2010.
DOI : 10.1016/j.obhdp.2009.11.001

U. Gneezy, S. Meier, R. , and P. , When and Why Incentives (Don't) Work to Modify Behavior, Journal of Economic Perspectives, vol.25, issue.4, pp.191-209, 2011.
DOI : 10.1257/jep.25.4.191
URL : https://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.25.4.191

U. Gneezy and A. Rustichini, Pay Enough or Don't Pay at All*, Quarterly Journal of Economics, vol.115, issue.3, pp.791-810, 2000.
DOI : 10.1162/003355300554917
URL : http://rady.ucsd.edu/faculty/directory/gneezy/docs/pay-enough.pdf

J. I. Gold and M. N. Shadlen, Neural computations that underlie decisions about sensory stimuli, Trends in Cognitive Sciences, vol.5, issue.1, pp.10-16, 2001.
DOI : 10.1016/S1364-6613(00)01567-9

J. I. Gold and M. N. Shadlen, The Neural Basis of Decision Making, Annual Review of Neuroscience, vol.30, issue.1, pp.535-574, 2007.
DOI : 10.1146/annurev.neuro.29.051605.113038

D. Green and J. Swets, Signal detection theory and psychophysics, 1966.

B. Greiner, Subject pool recruitment procedures: organizing experiments with ORSEE, Journal of the Economic Science Association, vol.94, issue.4, pp.114-125, 2015.
DOI : 10.1080/00221309.1976.9711593

M. J. Hautus, Corrections for extreme proportions and their biasing effects on estimated values ofd???, Behavior Research Methods, Instruments, & Computers, vol.36, issue.1, pp.46-51, 1995.
DOI : 10.1016/0022-2496(92)90037-8
URL : https://link.springer.com/content/pdf/10.3758%2FBF03203619.pdf

G. Hollard, S. Massoni, and J. Vergnaud, In search of good probability assessors: an experimental comparison of elicitation rules for confidence judgments, Theory and Decision, vol.30, issue.1, pp.363-387, 2016.
DOI : 10.1016/0030-5073(82)90237-9
URL : https://hal.archives-ouvertes.fr/hal-01306258

H. Levene, Robust tests for equality of variances. Contributions to probability and statistics: Essays in honor of Harold Hotelling, pp.278-292, 1960.

H. Levitt, Transformed Up???Down Methods in Psychoacoustics, The Journal of the Acoustical Society of America, vol.49, issue.2B, pp.467-477, 1971.
DOI : 10.1121/1.1912375

S. D. Mago, R. M. Sheremeta, and A. Yates, Best-of-three contest experiments: Strategic versus psychological momentum, International Journal of Industrial Organization, vol.31, issue.3, pp.31287-296, 2013.
DOI : 10.1016/j.ijindorg.2012.11.006

S. Massoni, T. Gajdos, and J. Vergnaud, Confidence measurement in the light of signal detection theory, Frontiers in Psychology, vol.26, issue.325, p.1455, 2014.
DOI : 10.1017/S0140525X03000086
URL : https://hal.archives-ouvertes.fr/hal-01239378

I. J. Myung and J. R. Busemeyer, Criterion learning in a deferred decision-making task. The American journal of psychology, pp.1-16, 1989.
DOI : 10.2307/1423113

J. Neyman and E. S. Pearson, On the Problem of the Most Efficient Tests of Statistical Hypotheses, Containing Papers of a Mathematical or Physical Character, pp.289-337, 1933.
DOI : 10.1098/rsta.1933.0009

C. R. Price and R. M. Sheremeta, Endowment effects in contests, Economics Letters, vol.111, issue.3, pp.217-219, 2011.
DOI : 10.1016/j.econlet.2011.02.003
URL : https://www.chapman.edu/ESI/wp/EndowmentEffectsInContests-Sheremeta.pdf

D. Rahnev and R. Denison, Suboptimality in perception, p.60194, 2017.

A. E. Roth and I. Erev, Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term, Games and Economic Behavior, vol.8, issue.1, pp.164-212, 1995.
DOI : 10.1016/S0899-8256(05)80020-X

S. Siegel, Theoretical models of choice and strategy behavior: Stable state behavior in the two-choice uncertain outcome situation, Psychometrika, vol.4, issue.4, pp.303-316, 1959.
DOI : 10.1080/00221325.1957.10532999

C. Starmer, Experiments in economics: should we trust the dismal scientists in white coats?, Journal of Economic Methodology, vol.8, issue.1, pp.1-30, 1999.
DOI : 10.1080/00224545.1931.9918964

C. Summerfield and K. Tsetsos, Building Bridges between Perceptual and Economic Decision-Making: Neural and Computational Mechanisms, Frontiers in Neuroscience, vol.6, 2012.
DOI : 10.3389/fnins.2012.00070
URL : http://journal.frontiersin.org/article/10.3389/fnins.2012.00070/pdf

A. Tversky and D. Kahneman, Loss aversion in riskless choice: A referencedependent model. The quarterly journal of economics, pp.1039-1061, 1991.
DOI : 10.2307/2937956
URL : http://www.sscnet.ucla.edu/polisci/faculty/chwe/austen/tversky1991.pdf

J. Tzelgov, D. Ganor-stern, and K. Maymon-schreiber, The representation of negative numbers: Exploring the effects of mode of processing and notation, The Quarterly Journal of Experimental Psychology, vol.52, issue.3, pp.62605-624, 2009.
DOI : 10.1037/0278-7393.26.1.103

P. P. Wakker, Explaining the characteristics of the power (crra) utility family. Health economics, pp.1329-1344, 2008.

P. P. Wakker, Prospect theory: For risk and ambiguity, 2010.
DOI : 10.1017/CBO9780511779329

T. D. Wickens, Elementary signal detection theory, 2001.
DOI : 10.1093/acprof:oso/9780195092509.001.0001

G. Wu and A. B. Markle, An Empirical Test of Gain-Loss Separability in Prospect Theory, Management Science, vol.54, issue.7, pp.1322-1335, 2008.
DOI : 10.1287/mnsc.1070.0846

D. J. Zizzo, Experimenter demand effects in economic experiments, Experimental Economics, vol.54, issue.1, pp.75-98, 2010.
DOI : 10.1257/jep.8.1.113

P. C. Fishburn and G. A. Kochenberger, TWO-PIECE VON NEUMANN-MORGENSTERN UTILITY FUNCTIONS, Decision Sciences, vol.47, issue.5, pp.503-518, 1979.
DOI : 10.2307/1880632

D. Kahneman and A. Tversky, Prospect Theory: An Analysis of Decision under Risk, Econometrica, vol.47, issue.2, pp.263-292, 1979.
DOI : 10.2307/1914185
URL : http://www.ma.utexas.edu/users/pmonin/mr/Inferring%20Preferences%203_1_09/Kahneman1.pdf

A. Reynaud and S. Couture, Stability of risk preference measures: results from a field experiment on French farmers, Theory and Decision, vol.36, issue.21, pp.203-221, 2012.
DOI : 10.1080/0003684042000280580

A. Tversky and D. Kahneman, Advances in prospect theory: Cumulative representation of uncertainty, Journal of Risk and Uncertainty, vol.55, issue.1, pp.297-323, 1992.
DOI : 10.1007/978-1-4613-9728-1_4

P. P. Wakker, V. Köbberling, and C. Schwieren, Prospect-theory???s Diminishing Sensitivity Versus Economics??? Intrinsic Utility of Money: How the Introduction of the Euro can be Used to Disentangle the Two Empirically, Theory and Decision, vol.2, issue.3, pp.205-231, 2007.
DOI : 10.1257/jel.38.2.332