I have begun to put together a Youtube channel. It is in it’s infancy, but I hope it will prove to be useful. You can find a complete index of the videos here along with links to websites that provide various analysis-specific resources (e.g., definitions, APA style write-ups, methods for determining sample size). Feedback is welcome!
Here is an interesting paper by Sayette and colleagues titled “A Person-Centered Analysis of Craving in Smoking-Cue-Exposure Research” published in Clinical Psychological Science. While its appears they did not use the OOM software, they did follow the approach to focusing on individual responses in our Persons as Effect Sizes paper.
I have published a paper titled Drawing Inferences from Randomization Tests. It is published here in Personality and Individual Differences. My hope in writing this paper was to describe the types of inferences one can draw from the randomization tests used in the OOM software. Here is the abstract:
Randomization tests grew out of permutation tests that were developed in the 1930s. Since then statisticians have expounded upon their nature as well as their various strengths and weaknesses. Uncertainty remains, however, with regard to the types of inferences that can be drawn from randomization tests, if indeed any type of inference can be drawn at all. In this paper we propose that randomization tests can play a role in drawing what are known as abductive inferences and inferences to best explanation from empirical research. Contemporary philosophers of science hold that such inferences are central to scientific reasoning; hence, randomization tests may serve as an effective bridge between the specific realm of statistical inference and the more general realm of scientific inference.
Speelman and McGann have published a paper in Frontiers titled “Statements About the Pervasiveness of Behavior Require Data About the Pervasiveness of Behavior.” This is a nice companion piece to our Persons as Effect Sizes paper. Generally, the argument we are all making is that one must be careful to focus on the individuals in one’s study. Aggregate statistics do not tell the entire story of one’s data. OOM can be used to analyze the data presented by Speelman and McGann, as their pervasiveness index is equivalent to the Percent Correct Classifications (PCC) index. They also discuss setting up thresholds for determining the number of people classified correctly according to expectation. In OOM this goal is accomplished with the Classification Imprecision option available in most analyses.
James Lamiell and Kate Slaney (Eds.) have published their new book, Problematic Research Practices and Inertia in Scientific Psychology: History, Sources, and Recommended Solutions. There are chapters on statistics, measurement, psychologists’ distaste for criticism, and the struggle to understand persons using aggregate methods. We have a chapter in which we use OOM to analyse data from a study on Dissociative Identity Disorder. We also address strategies to help connect mainstream researchers to OOM the ideas expressed in Lamiell and Slaney’s book.