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

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.