A novel CFA + EFA model to detect aberrant respondents
提出一种结合验证性和探索性因子分析的因子混合模型，用于识别社会调查中常见的虚假和随意作答的异常受访者，并通过模拟和案例验证了有效性。
Abstract Aberrant respondents are common but yet extremely detrimental to the quality of social surveys or questionnaires. Recently, factor mixture models (FMMs) have been employed to identify individuals providing deceptive or careless responses. We propose a comprehensive FMM for continuous outcomes that combines confirmatory and exploratory factor models to classify both the nonaberrant and aberrant respondents. The flexibility of the proposed classification model allows for the identification of two of the most common aberrant 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 dealing with aberrant responses in social and behavioural surveys.