Who r u?: On the (in)accuracy of incumbent-based estimates of range restriction in criterion-related and differential validity research.

Who r u?: On the (in)accuracy of incumbent-based estimates of range restriction in criterion-related and differential validity research.

Roth, Philip L;Le, Huy;Oh, In-Sue;Van Iddekinge, Chad H;Robbins, Steven B;
the journal of applied psychology 2017 Vol. 102 pp. 802-828
178
roth2017whothe

Abstract

Correcting validity estimates for selection procedures for range restriction typically involves comparing variance in predictor scores between all job applicants and applicants who were selected. However, some research on criterion-related and differential validity of cognitive ability tests has relied on range restriction corrections based on data from job incumbents. Unfortunately, there remains ambiguity concerning the accuracy of this incumbent-based approach vis-à-vis the applicant-based approach. To address this issue, we conducted several Monte Carlo simulations, as well as an analysis of college admissions data. Our first simulation study showed that incumbent-based range restriction corrections result in downwardly biased estimates of criterion-related validity, whereas applicant-based corrections were quite accurate. Our second set of simulations showed that incumbent-based range restriction corrections can produce evidence of differential validity when there is no differential validity in the population. In contrast, applicant-based corrections tended to accurately estimate population parameters and showed little, if any, evidence of differential validity when there is no differential validity in the population. Analysis of data for the ACT as a predictor of academic performance revealed similar patterns of bias for incumbent-based corrections in an academic setting. Overall, the present findings raise serious concerns regarding the use of incumbent-based range restriction corrections in lieu of applicant-based corrections. They also cast doubt on recent evidence for differential validity of predictors of job performance. (PsycINFO Database Record

Citation

ID: 43633
Ref Key: roth2017whothe
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
43633
Unique Identifier:
10.1037/apl0000193
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet