An introduction to good practices in cognitive modeling
By Andrew Heathcote, Scott D. Brown, Eric-Jan Wagenmakers. 2015
108 citations recorded by the source corpus.
Cognitive modeling can provide important insights into the underlying causes of behavior, but the validity of those insights rests on careful model development and checking. We provide guidelines on five important aspects of the practice of cognitive modeling: parameter recovery, testing selective influence of experimental manipulations on model parameters, quantifying uncertainty in parameter estimates, testing and displaying model fit, and selecting among different model parameterizations and types of models. Each aspect is illustrated with examples.
Subfields: Developmental and Educational Psychology, Experimental and Cognitive Psychology, General Decision Sciences
View Paper: https://www.semanticscholar.org/paper/5ddbcfb1d0a64b8fb85e61cc014f86b15505ca04
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In Developmental and Educational Psychology
In Experimental and Cognitive Psychology
In General Decision Sciences
Citations in the corpus
- Applying processing trees in social psychology (2016, methodology): “Bridging the gap requires an additional and extensive empirical validation program via selective-influence studies (Batchelder & Alexander, 2013; Heathcote et al., 2015).”
- Robust Modeling in Cognitive Science (2019, unknown): “that fit a model to data simulated from that model (Cook et al. 2006; Heathcote et al. 2015).”
- Ten simple rules for the computational modeling of behavioral data (2019, background): “…consult the many excellent tutorials, didactic examples, and books on the topic (Busemeyer and Diederich, 2010; Daw, 2011; Daw and Tobler, 2014; Heathcote et al., 2015; Huys, 2017; Turner et al., 2013; Vandekerckhove et al., 2015; Wagenmakers and Farrell, 2004; Rigoux et al., 2014; Nilsson et…”