Mixture Item Response Models for Inattentive Responding Behavior
提出一种新的混合项目反应理论模型，用于区分不认真作答与正常作答，模拟和实证表明该模型能有效识别不认真反应，避免参数估计偏差。
Inattentive responses can threaten measurement quality, yet they are common in rating- or Likert-scale data. In this study, we proposed a new mixture item response theory model to distinguish inattentive responses from normal responses so that test validity can be ascertained. Simulation studies demonstrated that the parameters of the new model were recovered fairly well using the Bayesian methods implemented in the freeware WinBUGS, and fitting the new model to data that lacked inattentive responses did not result in severely biased parameter estimates. In contrast, ignoring inattentive responses by fitting standard item response theory models to data containing inattentive responses yielded seriously biased parameter estimates and a failure to distinguish inattentive participants from normal participants; the person-fit statistic l z was also unsatisfactory in identifying inattentive responses. Two empirical examples demonstrate the applications of the new model.