Aberrant respondents are common but yet extremely detrimental to the quality of social surveys or questionnaires. Recently, factor mixture models have been employed to identify individuals providing deceptive or careless responses. We propose a comprehensive factor mixture model that combines confirmatory and exploratory factor models to represent both the non-aberrant and aberrant components of the responses. The flexibility of the proposed solution allows for the identification of two of the most common aberant response styles, namely faking and careless responding. We validated our approach by means of two simulations and two case studies. The results indicate the effectiveness of the proposed model in handling with aberrant responses in social and behavioral surveys.

翻译：异常受访者在社会调查或问卷中普遍存在，且对数据质量具有极大危害。近年来，因子混合模型已被用于识别提供欺骗性或粗心回答的个体。我们提出了一种综合性的因子混合模型，该模型结合了验证性因子模型和探索性因子模型，分别表征回答中的正常成分与异常成分。所提方案的灵活性使其能够识别两种最常见的异常应答模式，即虚假作答和粗心作答。我们通过两项模拟研究和两项案例研究验证了该方法的有效性。结果表明，所提模型在处理社会与行为调查中的异常应答方面效果显著。