Floor effect

In statistics, a floor effect (also known as a basement effect) arises when a data-gathering instrument has a lower limit to the data values it can reliably specify.[1] This lower limit is known as the "floor".[2] The "floor effect" is one type of scale attenuation effect;[3] the other scale attenuation effect is the "ceiling effect". Floor effects are occasionally encountered in psychological testing, when a test designed to estimate some psychological trait has a minimum standard score that may not distinguish some test-takers who differ in their responses on the test item content.[4] Giving preschool children an IQ test designed for adults would likely show many of the test-takers with scores near the lowest standard score for adult test-takers (IQ 40 on most tests that were currently normed as of 2010). To indicate differences in current intellectual functioning among young children, IQ tests[5] specifically for young children are developed, on which many test-takers can score well above the floor score. An IQ test designed to help assess intellectually disabled persons might intentionally be designed with easier item content and a lower floor score to better distinguish among individuals taking the test as part of an assessment process.[6]

References

1. Lim, Christopher R.; Harris, Kristina; Dawson, Jill; Beard, David J.; Fitzpatrick, Ray; Price, Andrew J. (2015-07-01). "Floor and ceiling effects in the OHS: an analysis of the NHS PROMs data set". BMJ Open. 5 (7): e007765. doi:10.1136/bmjopen-2015-007765. ISSN 2044-6055. PMC 4521553. PMID 26216152.
2. Stephanie (2017-09-10). "Floor Effect / Basement Effect: Definition". Statistics How To. Retrieved 2020-04-14.
3. "Scale Attenuation Effect - SAGE Research Methods". methods.sagepub.com. Retrieved 2020-10-22.
4. Zhu, Leina; Gonzalez, Jorge (2017). "Modeling Floor Effects in Standardized Vocabulary Test Scores in a Sample of Low SES Hispanic Preschool Children under the Multilevel Structural Equation Modeling Framework". Frontiers in Psychology. 8: 2146. doi:10.3389/fpsyg.2017.02146. ISSN 1664-1078. PMC 5732956. PMID 29312033.
5. Sansone, Stephanie M; Schneider, Andrea; Bickel, Erika; Berry-Kravis, Elizabeth; Prescott, Christina; Hessl, David (2014). "Improving IQ measurement in intellectual disabilities using true deviation from population norms". Journal of Neurodevelopmental Disorders. 6 (1): 16. doi:10.1186/1866-1955-6-16. ISSN 1866-1947. PMC 4613563. PMID 26491488.
6. "IQ testing in individuals with intellectual disability". health.ucdavis.edu. Retrieved 2020-04-14.

Further reading

• Everitt, B.S. (2002) The Cambridge dictionary of Statistics, Second Edition. CUP. ISBN 0-521-81099-X
• Sternberg, Robert J., ed. (2000). Handbook of Intelligence. Cambridge: Cambridge University Press. p. 456. ISBN 978-0-521-59648-0. Lay summary (22 July 2013).
• Weiss, Lawrence G.; Saklofske, Donald H.; Coalson, Diane; Raiford, Susan, eds. (2010). WAIS-IV Clinical Use and Interpretation: Scientist-Practitioner Perspectives. Practical Resources for the Mental Health Professional. Alan S. Kaufman (Foreword). Amsterdam: Academic Press. p. 8. ISBN 978-0-12-375035-8. Lay summary (16 August 2010).
• Groth-Marnat, Gary (2009). Handbook of Psychological Assessment (Fifth ed.). Hoboken (NJ): Wiley. ISBN 978-0-470-08358-1. Lay summary (11 September 2010).