Identifying Cheating on Unproctored Internet Tests: The Z-test and the likelihood ratio test

Jing Guo, Fritz Drasgow

Research output: Contribution to journalArticlepeer-review

Abstract

Unproctored Internet testing (UIT) is becoming more popular in employment settings due to its cost effectiveness and efficiency. However, one of the major concerns with UIT is the possibility of cheating behaviors: a more capable conspirator can sit beside the real applicant and answer test items, or the applicant may use unauthorized materials. The present study examined the effectiveness of using a proctored verification test following the UIT to identify cheating in UIT, where 2 test statistics, a Z-test and a likelihood ratio (LR) test, compare the consistency of test performance across the testing conditions. A simulation study was conducted to test the effectiveness of the two test statistics for a computerized adaptive test format. Results indicate that both test statistics have high power to detect dishonest job applicants at low Type I error rates. Compared with the LR test, the Z-test was more efficient and effective and is therefore recommended for practical applications. The theoretical and practical implications are discussed.

Original languageEnglish (US)
Pages (from-to)351-364
Number of pages14
JournalInternational Journal of Selection and Assessment
Volume18
Issue number4
DOIs
StatePublished - Dec 1 2010

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Applied Psychology
  • Psychology(all)
  • Strategy and Management
  • Management of Technology and Innovation

Fingerprint Dive into the research topics of 'Identifying Cheating on Unproctored Internet Tests: The Z-test and the likelihood ratio test'. Together they form a unique fingerprint.

Cite this