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  "Title": "Temporal Discounting Models",
  "Description": "Tools for working with temporal discounting data, designed\nfor behavioural researchers to simplify data cleaning/scoring\nand model fitting. The package implements widely used methods\nsuch as computing indifference points from adjusting amount\ntask (Frye et al., 2016, <doi:10.3791/53584>), testing for\nnon-systematic discounting per the criteria of Johnson & Bickel\n(2008, <doi:10.1037/1064-1297.16.3.264>), scoring\nquestionnaires according to the methods of Kirby et al. (1999,\n<doi:10.1037//0096-3445.128.1.78>) and Wileyto et al (2004,\n<doi:10.3758/BF03195548>), Bayesian model selection using a\nrange of discount functions (Franck et al., 2015,\n<doi:10.1002/jeab.128>), drift diffusion models of discounting\n(Peters & D'Esposito, 2020,\n<doi:10.1371/journal.pcbi.1007615>), and model-agnostic\nmeasures of discounting such as area under the curve (Myerson\net al., 2001, <doi:10.1901/jeab.2001.76-235>) and ED50 (Yoon &\nHiggins, 2008, <doi:10.1016/j.drugalcdep.2007.12.011>).",
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        "Computing indifference points",
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        "Kirby scoring",
        "Wileyto scoring",
        "Newer methods",
        "Linear models",
        "Nonlinear models",
        "Choice rules",
        "Error rates",
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