Theoretically informed generative models can advance the psychological and brain sciences: Lessons from the reliability paradox
Theories of individual differences are foundational to psychological and brain sciences, yet
they are traditionally developed and tested using superficial summaries of data (eg, mean …
they are traditionally developed and tested using superficial summaries of data (eg, mean …
Adaptive design optimization as a promising tool for reliable and efficient computational fingerprinting
A key challenge in understanding mental (dys) functions is their etiological and functional
heterogeneity, and several multidimensional assessments have been proposed for their …
heterogeneity, and several multidimensional assessments have been proposed for their …
[PDF][PDF] Learning from the reliability paradox: How theoretically informed generative models can advance the social, behavioral, and brain sciences
A primary aim of social, behavioral, and brain sciences is to develop explanations that
answer questions of why or how observed psychological phenomena occur (Hempel & …
answer questions of why or how observed psychological phenomena occur (Hempel & …
Digital learning games for mathematics and computer science education: The need for preregistered RCTs, standardized methodology, and advanced technology
L Bertram - Frontiers in Psychology, 2020 - frontiersin.org
In today's digital information society, mathematical and computational skills are becoming
increasingly important. With the demand for mathematical and computational literacy rising …
increasingly important. With the demand for mathematical and computational literacy rising …
Prince: An improved method for measuring incentivized preferences
This paper introduces the Prince incentive system for measuring preferences. Prince
combines the tractability of direct matching, allowing for the precise and direct elicitation of …
combines the tractability of direct matching, allowing for the precise and direct elicitation of …
A systematic investigation into the reliability of inter-temporal choice model parameters
Decades of work have been dedicated to developing and testing models that characterize
how people make inter-temporal choices. Although parameter estimates from these models …
how people make inter-temporal choices. Although parameter estimates from these models …
Utility of computational approaches for precision psychiatry: Applications to substance use disorders
Revolutionary advances in neuroscience and genetics over the past two decades have
provided unprecedented opportunities for increasing our understanding of the etiology and …
provided unprecedented opportunities for increasing our understanding of the etiology and …
Rumination derails reinforcement learning with possible implications for ineffective behavior
How does rumination affect reinforcement learning—the ubiquitous process by which
people adjust behavior after error to behave more effectively in the future? In a within …
people adjust behavior after error to behave more effectively in the future? In a within …
Knowing what to know: Implications of the choice of prior distribution on the behavior of adaptive design optimization
Adaptive design optimization (ADO) is a state-of-the-art technique for experimental design
(Cavagnaro, Myung, Pitt, & Kujala, 2010). ADO dynamically identifies stimuli that, in …
(Cavagnaro, Myung, Pitt, & Kujala, 2010). ADO dynamically identifies stimuli that, in …
Data-driven experimental design and model development using Gaussian process with active learning
Interest in computational modeling of cognition and behavior continues to grow. To be most
productive, modelers should be equipped with tools that ensure optimal efficiency in data …
productive, modelers should be equipped with tools that ensure optimal efficiency in data …