A Mixture Response Time Process Model for Aberrant Behavior and Item Nonresponses

• Activity Number: 380 - Advances in Statistical Learning for Large-Scale and Multidimensional Testing Data
• Type: Topic-Contributed
• Date/Time: Thursday, August 12, 2021 : 12:00 PM to 1:50 PM
• Sponsor: International Chinese Statistical Association
• Author(s): Jing Lu* and Chun Wang
• Companies: Northeast Normal University and University of Washington
• Keywords: item response theory; mixture model; response time modeling; aberrant behavior; educational measurement

Abstract

In high-stakes, large-scale, standardized tests with certain time limits, examinees are likely to engage in either one of the three types of behavior: solution behavior, rapid guessing behavior, and cheating behavior. Oftentimes examinees do not always respond solve to all items due to various reasons such as time limit or test-taking strategy even when solution behavior occurs. Item nonresponses maybe happen due to intentionally omitting some items (omitted responses) or due to lack of time (not-reached responses), which. Both types are related to latent abilities and hence the missingness is nonignorable. In this paper, we proposed an innovative mixture response time process model to detect two most common aberrant behaviors: rapid guessing behavior and cheating behavior, meanwhile, a response time process model as a cohesive missing data model to account for two types of item nonresponses: not-reached items and omitted items. Simulation results show that the new method yields accurate item and person parameter estimates, as well as high true detection rate and low false detection rate. A real data example is provided in the end.