A tutorial on adaptive design optimization

• Introduces the reader to adaptive design optimization (ADO).
• ADO is a Bayesian statistical framework for optimizing experimental designs.
• Provides the conceptual, theoretical, and computational foundations of ADO.
• Serves as a practical guide to applying ADO to simple cognitive models.

Experimentation is ubiquitous in the field of psychology and fundamental to the advancement of its science, and one of the biggest challenges for researchers is designing experiments that can conclusively discriminate the theoretical hypotheses or models under investigation. The recognition of this challenge has led to the development of sophisticated statistical methods that aid in the design of experiments and that are within the reach of everyday experimental scientists. This tutorial paper introduces the reader to an implementable experimentation methodology, dubbed Adaptive Design Optimization, that can help scientists to conduct “smart” experiments that are maximally informative and highly efficient, which in turn should accelerate scientific discovery in psychology and beyond.