Theory Methods Lab
This project is dedicated to articulating a particular way in which scientific theories explain phenomena; specifically, productive explanation. We postulate that a theory explains a phenomenon when the phenomenon to be explained, when expressed as a pattern in data, is produced by a formal model that instantiates the scientific theory. Furthermore, we devise criteria and checks to assess the quality of such explanations.
This project is dedicated to designing and testing procedures for a crowd-sourcing approach to theory formalization; a many modelers approach for theory development instead of a many-analysts approach for statistical inference. In particular, we are working on guidelines and assessment methods for differential formalization of the same verbal theory by N>2 teams of modelers.
This project develops a systematic way to evaluate the explanatory quality of a theory based on an extension of Paul Thagard’s model for explanatory coherence. The approach allows the user to specify explanatory relations between theoretical postulates (e.g., general intelligence causes individual differences on cognitive tests) and empirical phenomena (e.g., cognitive tests are positively correlated). Subsequently, an Ising model is used to express the degree to which the system of theory and phenomena exhibits explanatory coherence.
Book of Empirical Phenomena
Empirical phenomena are stable, robust features of the world (e.g., empirical generalizations like “all cognitive tests correlate positively” or “females are more often diagnosed with clinical depression than males”) that form explanatory targets for scientific theories. In the framework of theory construction methodology, we represent empirical phenomena as generalized statistical patterns. This project documents robust empirical phenomena in psychological science and represents them in terms of statistical patterns that formal models can use as benchmarks to assess their explanatory qualities against
This project is dedicated to developing a collaborative approach to formal theory construction. We envision this as follows: First, we find (or they come to us) scientists from any area of psychology who have phenomena to explain, but no clear theory to explain them with. Second, we bring in theorists from related (or relevant distant) fields and modelers with expertise we expect to be pertinent. Then, these people are brought together over the course of several sessions where phenomena are assessed, verbal theory is explicated, and theory formalization is attempted. Roughly, such theory jams are considered successful when a) the formal model captures the verbal according to the scientists; b) it capable of producing the phenomena that were to be explained; and c) novel and testable hypotheses can be derived from it. Subsequently, an Ising model is used to express the degree to which the system of theory and phenomena exhibits explanatory coherence.