Computational modeling is now ubiquitous in psychology, and researchers who are not
modelers may find it increasingly difficult to follow the theoretical developments in their field …

Computational Modelling in Psychology introduces the principles of using computational
models in psychology and provides a clear idea about how model construction, parameter …

Hierarchical Bayesian modeling provides a flexible and interpretable way of extending
simple models of cognitive processes. To introduce this special issue, we discuss four of the …

Cognitive Modeling is the first book to provide students with an easy-to understand
introduction to the basic methods used to build and test cognitive models. Authors Jerome R …

This article reviews current methods for evaluating models in the cognitive sciences,
including theoretically based approaches, such as Bayes factors and minimum description …

Bayesian inference has become a standard method of analysis in many fields of science.
Students and researchers in experimental psychology and cognitive science, however, have …

Model selection should be based not solely on goodness-of-fit, but must also consider
model complexity. While the goal of mathematical modeling in cognitive psychology is to …

Proponents of Bayesian statistical methods argue that these methods provide a complete
and coherent framework for the basic chal-lenge of relating scientific models to data …

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 …

Bayesian data analysis involves describing data by meaningful mathematical models, and
allocating credibility to parameter values that are consistent with the data and with prior …