Inferring causal networks from observations and interventions. - Mark Steyvers; Joshua B. Tenenbaum; Eric-Jan Wagenmakers; Ben Blum (Cogn. Sci., 2003)

Comparison of Decision Learning Models Using the Generalization Criterion Method. - Woo-Young Ahn; Jerome R. Busemeyer; Eric-Jan Wagenmakers; Julie C. Stout (Cogn. Sci., 2008)

A Survey of Model Evaluation Approaches With a Tutorial on Hierarchical Bayesian Methods. - Richard M. Shiffrin; Michael D. Lee 001; Woojae Kim; Eric-Jan Wagenmakers (Cogn. Sci., 2008)

The Effects of Accessory Stimuli on Information Processing: Evidence from Electrophysiology and a Diffusion Model Analysis. - Marieke Jepma; Eric-Jan Wagenmakers; Guido P. H. Band; Sander Nieuwenhuis (J. Cogn. Neurosci., 2009)

An encompassing prior generalization of the Savage-Dickey density ratio. - Ruud Wetzels; Raoul P. P. P. Grasman; Eric-Jan Wagenmakers (Comput. Stat. Data Anal., 2010)

A Phase Transition Model for the Speed-Accuracy Trade-Off in Response Time Experiments. - Gilles Dutilh; Eric-Jan Wagenmakers; Ingmar Visser; Han L. J. van der Maas (Cogn. Sci., 2011)

Context Effects in Multi-Alternative Decision Making: Empirical Data and a Bayesian Model. - Guy Hawkins; Scott D. Brown; Mark Steyvers; Eric-Jan Wagenmakers (Cogn. Sci., 2012)

Abstract Concepts Require Concrete Models: Why Cognitive Scientists Have Not Yet Embraced Nonlinearly Coupled, Dynamical, Self-Organized Critical, Synergistic, Scale-Free, Exquisitely Context-Sensitive, Interaction-Dominant, Multifractal, Interdependent Brain-Body-Niche Systems. - Eric-Jan Wagenmakers; Han L. J. van der Maas; Simon Farrell (Top. Cogn. Sci., 2012)

A Comparison of Reinforcement Learning Models for the Iowa Gambling Task Using Parameter Space Partitioning. - Helen Steingroever; Ruud Wetzels; Eric-Jan Wagenmakers (J. Probl. Solving, 2013)

A Bayesian framework for simultaneously modeling neural and behavioral data. - Brandon M. Turner; Birte U. Forstmann; Eric-Jan Wagenmakers; Scott D. Brown; Per B. Sederberg; Mark Steyvers (NeuroImage, 2013)

Is There a Free Lunch in Inference? - Jeffrey N. Rouder; Richard D. Morey; Josine Verhagen; Jordan M. Province; Eric-Jan Wagenmakers (Top. Cogn. Sci., 2016)

Interpreting nonsignificant findings in psychological research. - Bence Palfi; Aba Szollosi; Barnabas Szaszi; Marton Kovacs; Mark Zrubka; Péter Szécsi; Balazs Aczel; Eric-Jan Wagenmakers (CogSci, 2017)

Bayesian Evidence Accumulation in Experimental Mathematics: A Case Study of Four Irrational Numbers. - Quentin F. Gronau; Eric-Jan Wagenmakers (Exp. Math., 2018)

Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models. - Daniel W. Heck; Antony M. Overstall; Quentin F. Gronau; Eric-Jan Wagenmakers (Stat. Comput., 2019)

Bayesian Inference in Numerical Cognition: A Tutorial Using JASP. - Thomas J. Faulkenberry; Alexander Ly; Eric-Jan Wagenmakers (J. Numer. Cogn., 2020)

JASP for Audit: Bayesian Tools for the Auditing Practice. - Koen Derks; Jacques de Swart; Eric-Jan Wagenmakers; Jan Wille; Ruud Wetzels (J. Open Source Softw., 2021)

Informed Bayesian Inference for the A/B Test. - Quentin F. Gronau; Akash Raj K. N.; Eric-Jan Wagenmakers (J. Stat. Softw., 2021)

BFpack: Flexible Bayes Factor Testing of Scientific Theories in R. - Joris Mulder; Donald R. Williams; Xin Gu; Andrew Tomarken; Florian Böing-Messing; Anton Olsson-Collentine; Marlyne Meijerink; Janosch Menke; Robbie van Aert; Jean-Paul Fox; Herbert Hoijtink; Yves Rosseel; et al. (J. Stat. Softw., 2021)

Flexible yet fair: blinding analyses in experimental psychology. - Gilles Dutilh; Alexandra Sarafoglou; Eric-Jan Wagenmakers (Synth., 2021)