Regression to the Mean

 

Regression to the mean is a statistical concept based on evidence that a sample of data representing extreme values from the population mean will likely be close to the mean the next time a sample is taken.

In psychological testing, people who obtain extreme scores on a test tend to obtain scores closer to the mean on a second testing. That is, high scorers tend to earn lower scores and low scorers tend to earn higher scores.

The term, Regression to the Mean is sometimes referred to as RTM. The concept appears in a paper by British scientist Sir Francis Galton (1886).

Cite this post

Sutton, G. W. (2024, January 5). Regression to the mean. Psychology Concepts and Theories. Retrieved from https://suttonpsychology.blogspot.com/2024/01/regression-to-mean.html

References

Galton, F. (1886). Regression towards mediocrity in hereditary stature. The Journal of the Anthropological Institute of Great Britain and Ireland, 15, 246-263.

Sutton, G. W. (2024, January 5). Regression to the mean. Psychology Concepts and Theories. Retrieved from https://suttonpsychology.blogspot.com/2024/01/regression-to-mean.html

Geoffrey W. Sutton, PhD is Emeritus Professor of Psychology. He retired from a clinical practice and was credentialed in clinical neuropsychology and psychopharmacology. His website is  www.suttong.com

 

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Brier scores

 Brier scores reflect the accuracy of a probability forecast. The scores range from 0 to 1.0. A perfect prediction = 0 meaning complete or total accuracy.

Brier scores are named for Glenn W. Brier

For an example of Brier scores in research, see the metamemory study by Parlett-Pelleriti et al. (2021).

See also a discussion of Brier scores in the book, Noise.

Reference
Kahneman, D., Sibony, O., & Sunstein, C.R. (2021). Noise: A flaw in human judgment. New York: Hatchette.

Parlett-Pelleriti, C., Lin, G., Jones, M., Linstead, E. & Jaeggi, S. (2019). Exploring Age-Related Metamemory Differences using Modified Brier Scores and Hierarchical Clustering. Open Psychology, 1(1), 215-238. https://doi.org/10.1515/psych-2018-0015

broken-leg principle in psychology

 

The concept of a broken-leg principle refers to statistical models that clarify when the model is valid and when it is not.

An example, could be the likely prediction that a person will attend an event unless they have a broken leg or some other accident, which nullifies the prediction.

Researchers do well to clarify the conditions under which their models are valid and when their models should not be applied.

Please check out my website   www.suttong.com

   and see my books on   AMAZON       or  GOOGLE STORE

Also, consider connecting with me on    FACEBOOK   Geoff W. Sutton    

   TWITTER  @Geoff.W.Sutton    

You can read many published articles at no charge:

  Academia   Geoff W Sutton     ResearchGate   Geoffrey W Sutton