Dr. Frank Arocha has just published an article on scientific realism in the journal Theory & Psychology. The title of the article is: Scientific Realism and the Issue of Variability in Behavior. Here’s a link to the abstract:
The paper is broad in scope and offers a clear exposition of important issues facing modern psychologists and how we might move forward from a realist perspective. This will be required reading in my courses at OSU.
A new version of the OOM software has been uploaded. A number of minor bugs have been removed from the program, and a new option for generating data from proportions and frequencies (contingency tables) has been added. A video demonstrating this new feature has been uploaded to the Instructional Videos page (see link to the right, or click here). Two new videos for editing multigrams have also been added.
A sincere word of thanks to the faculty and staff of West Texas A&M University for hosting a talk on OOM last Friday, February 14th. I am particularly appreciative of John Richeson (an OSU alumnus!) and Mark Garrison for making the visit possible. West Texas A&M is growing and has a strong core of faculty…and, as a personally relevant fact, the university has an outstanding bowling program!
Thanks to Mark Garrison for the link to this N of 1 article. Science is the search for the causal structure of the world, and the history of science shows clearly that, while randomized trials can be useful, they are not necessary to gain such causal knowledge.
Thanks to Paul Barrett for alerting us to this newly published paper: Saylors, R., & Trafimow, D. (2020). Why the increasing use of complex causal models is a problem: On the danger sophisticated theoretical narratives pose to truth. Organizational Research Methods (https://doi.org/10.1177/1094428119893452 ), In Press, , 1-14. [paywall]
As pointed out by the authors, “As use of complex models increases, the joint probability a published model is true decreases.”
The paper comes with a calculator to compute said probability:
An analogous concern in OOM is that as a path model increases in complexity, fewer and fewer individuals will be traceable through the model. It is easy to imagine a complex path model in which not a single person can be accurately traced through all of the links. What use would such a model be as an explication of causes and effects? Of course, this information can only be known if the researcher attempts to perform such person-centered analyses.