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dc.contributor.advisor Oswald, Frederick L.
dc.creatorErcan, Seydahmet
dc.date.accessioned 2012-09-06T04:35:08Z
dc.date.accessioned 2012-09-06T04:35:11Z
dc.date.available 2012-09-06T04:35:08Z
dc.date.available 2012-09-06T04:35:11Z
dc.date.created 2012-05
dc.date.issued 2012-09-05
dc.date.submitted May 2012
dc.identifier.urihttps://hdl.handle.net/1911/64689
dc.description.abstract The current study examines the behaviors of four adverse impact measurements: the 4/5ths rule, two tests of significance (ZD and ZIR), and a newly developed AI measurement (Lnadj). Upon the suggestion of the Office of Federal Contract Compliance Program Manual about the sensitivity of the assessment of AI when the sample size is very large (Office of Federal Contract Compliance Programs, 2002), Lnadj is a new statistic that has been developed and proposed as an alternative practical significance test to the 4/5ths rule. The results indicated that, unlike the 4/5ths rule and other tests for adverse impact, Lnadj is an index of practical significance that is less sensitive to differences across selection conditions that are not supposed to affect tests of adverse impact. Furthermore, Lnadj decreases Type I error rates when there is a small d value and Type II error rates when there is moderate to large d value.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectAdverse Impact
Employee Selection
Four-Fifths Rule
Practical Significance
Simulation
Alternative rule
dc.title Assessing Adverse Impact: An Alternative to the Four-Fifths Rule
dc.contributor.committeeMember Beier, Margaret E.
dc.contributor.committeeMember Villado, Anton J.
dc.date.updated 2012-09-06T04:35:11Z
dc.identifier.slug 123456789/ETD-2012-05-163
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Psychology
thesis.degree.discipline Social Sciences
thesis.degree.grantor Rice University
thesis.degree.level Masters
thesis.degree.name Master of Arts
dc.identifier.citation Ercan, Seydahmet. "Assessing Adverse Impact: An Alternative to the Four-Fifths Rule." (2012) Master’s Thesis, Rice University. https://hdl.handle.net/1911/64689.


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