NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Hong, Maxwell; Rebouças, Daniella A.; Cheng, Ying – Journal of Educational Measurement, 2021
Response time has started to play an increasingly important role in educational and psychological testing, which prompts many response time models to be proposed in recent years. However, response time modeling can be adversely impacted by aberrant response behavior. For example, test speededness can cause response time to certain items to deviate…
Descriptors: Reaction Time, Models, Computation, Robustness (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
Hong, Maxwell; Steedle, Jeffrey T.; Cheng, Ying – Educational and Psychological Measurement, 2020
Insufficient effort responding (IER) affects many forms of assessment in both educational and psychological contexts. Much research has examined different types of IER, IER's impact on the psychometric properties of test scores, and preprocessing procedures used to detect IER. However, there is a gap in the literature in terms of practical advice…
Descriptors: Responses, Psychometrics, Test Validity, Test Reliability
Peer reviewed Peer reviewed
Direct linkDirect link
Liu, Yue; Cheng, Ying; Liu, Hongyun – Educational and Psychological Measurement, 2020
The responses of non-effortful test-takers may have serious consequences as non-effortful responses can impair model calibration and latent trait inferences. This article introduces a mixture model, using both response accuracy and response time information, to help differentiating non-effortful and effortful individuals, and to improve item…
Descriptors: Item Response Theory, Test Wiseness, Response Style (Tests), Reaction Time
Peer reviewed Peer reviewed
Direct linkDirect link
Patton, Jeffrey M.; Cheng, Ying; Hong, Maxwell; Diao, Qi – Journal of Educational and Behavioral Statistics, 2019
In psychological and survey research, the prevalence and serious consequences of careless responses from unmotivated participants are well known. In this study, we propose to iteratively detect careless responders and cleanse the data by removing their responses. The careless responders are detected using person-fit statistics. In two simulation…
Descriptors: Test Items, Response Style (Tests), Identification, Computation