Statistics How To

Incremental Validity

Validity >

Incremental validity refers to the additional benefit a particular predictor variable has above other predictors.

Incremental Validity in Practice

An example of incremental validity:
Let’s say a medical practitioner is more likely to correctly diagnose a kidney infection if a urine test is ordered, rather than relying on a physical examination and discussion of symptoms alone. We can say that the urine test has incremental validity.

If running a blood test in addition to the urine test gives the medical practitioner a further advantage, the blood test would also have incremental validity. But if the combination of blood test, urine test, and physical exam/interview has no higher predictive power than just the urine test and physical exam/interview, we would say that the blood test has no incremental validity in that situation.

Note that this type of validity depends not only on the variable in question, but also on the predictors which make up the base set. Both the situation and the predictors in the base set must be well defined for incremental validity to be a meaningful concept.

Estimating Incremental Validity

Hierarchical multiple regression is the technique most used to asses the amount of variability a predictor explains. This is often done by fitting a model to the data without the variable of interest, and then afterward adding in the focal variable and fitting a new model. The two models are compared (by calculating the R-squares statistic); and a significant change is understood to mean that the new variable does indeed have significant incremental validity, or additional predictive power.

References

Meyer, Rustin D. Incr. Validity In Encyclopedia of Industrial and Organizational Psychology,
Edited by Steven G. Rogelberg. DOI: http://dx.doi.org/10.4135/9781412952651.n130. Retrieved from http://sk.sagepub.com/reference/organizationalpsychology/n141.xml on August 3, 2018.

Hogan. Research Summary: Incr. Validity. Retrieved from https://cdn2.hubspot.net/hubfs/153377/a_Research/Incremental%20Validity%20RS%20111114%5B1%5D%20(1).pdf on August 3, 2018.

Westfall and Yarkoni. Running Head: Incr. Validity: Statistically controlling for confounding constructs is harder than you think. Retrieved from http://pilab.psy.utexas.edu/publications/Westfall_PLOS_ONE_2016.pdf on August 3, 2018.

Bridgeman, Brent. Essays and Multiple-Choice Tests as Predictors of College Freshman GPA.
Research in Higher Education. Vol. 32, No. 3 (June 1991), pp. 319-332. Retrieved from https://www.jstor.org/stable/40195972 on August 3, 2018.

Incr. Validity. Retrieved from
https://psychology.iresearchnet.com/industrial-organizational-psychology/i-o-psychology-theories/incremental-validity/ on August 3, 2018.

------------------------------------------------------------------------------

Need help with a homework or test question? With Chegg Study, you can get step-by-step solutions to your questions from an expert in the field. Your first 30 minutes with a Chegg tutor is free!

Statistical concepts explained visually - Includes many concepts such as sample size, hypothesis tests, or logistic regression, explained by Stephanie Glen, founder of StatisticsHowTo.

Comments? Need to post a correction? Please post a comment on our Facebook page.

Check out our updated Privacy policy and Cookie Policy