In low-stakes assessments, test performance has few or no consequences for examinees themselves, so that examinees may not be fully engaged when answering the items. Instead of engaging in solution behaviour, disengaged examinees might randomly guess or generate no response at all. When ignored, examinee disengagement poses a severe threat to the validity of results obtained from low-stakes assessments. Statistical modelling approaches in educational measurement have been proposed that account for non-response or for guessing, but do not consider both types of disengaged behaviour simultaneously. We bring together research on modelling examinee engagement and research on missing values and present a hierarchical latent response model for identifying and modelling the processes associated with examinee disengagement jointly with the processes associated with engaged responses. To that end, we employ a mixture model that identifies disengagement at the item-by-examinee level by assuming different data-generating processes underlying item responses and omissions, respectively, as well as response times associated with engaged and disengaged behaviour. By modelling examinee engagement with a latent response framework, the model allows assessing how examinee engagement relates to ability and speed as well as to identify items that are likely to evoke disengaged test-taking behaviour. An illustration of the model by means of an application to real data is presented.

中文翻译：

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一种分层潜在反应模型，用于在猜测和项目级无反应方面对考生参与进行推断。

在低风险评估中，考试成绩对考生本身影响很小或没有影响，因此考生在回答问题时可能不会完全投入。与参与解决方案行为不同，不参与的考生可能会随机猜测或根本不产生任何反应。当被忽视时，考生的脱离会对从低风险评估中获得的结果的有效性构成严重威胁。已经提出了教育测量中的统计建模方法，用于解释不响应或猜测，但不会同时考虑两种类型的脱离行为。我们汇集了对考生参与建模和缺失值研究的研究，并提出了一个分层潜在响应模型，用于识别和建模与考生脱离相关的过程以及与参与响应相关的过程。为此，我们采用了一个混合模型，通过假设不同的数据生成过程分别作为项目响应和遗漏的基础，以及与参与和脱离行为相关的响应时间，来识别逐个考生级别的脱离参与。通过使用潜在响应框架对考生参与进行建模，该模型允许评估考生参与与能力和速度的关系，以及识别可能引起不参与应试行为的项目。