摘要
混合模型方法(Mixture Model Method)是近年来提出的,对心理与教育测验中的异常作答进行处理的方法。与反应时阈值法,反应时残差法等传统方法相比,混合模型方法可以同时完成异常作答的识别和模型参数估计,并且,在数据污染严重的情况下仍具有较好的表现。该方法的原理为根据正常作答和异常作答的特点,针对分类潜变量(即作答层面的分类)的不同类别,在作答反应和(或)反应时部分建立不同的模型,从而实现对分类潜变量,以及模型中其他题目和被试参数的估计。文章详细介绍了目前提出的几种混合模型方法,并将其与传统方法比较分析。未来研究可在模型前提假设违背,含有多种异常作答等情况下探索混合模型方法的稳健性和适用性,通过固定部分题目参数,增加选择流程等方式提高混合模型方法的使用效率。
The mixture model method(MMM)is a new method proposed to handle data contaminated by aberrant responses in psychological and educational measurement.Compared to the traditional response time threshold methods and the response time residual methods,MMM shows the following advantages:(1)MMM detects aberrant responses and obtaining parameter estimates simultaneously;(2)it precisely recovers the severity of aberrant responding.Through building different item response models and response time models for different latent groups,MMM helps to identify aberrant responses from normal responses.Future researches could investigate the performance of MMM when its assumptions are violated or using data with other types of aberrant response patterns.The computation efficiency of MMM is also likely to be improved by fixing part of the item parameter estimates or by using an optimal way of choosing suitable methods.
作者
刘玥
刘红云
LIU Yue;LIU Hongyun(Institute of Brain and Psychological Sciences,Sichuan Normal University,Chengdu 610066,China;Beijing Key Laboratory of Applied Experimental Psychology,Beijing Normal University,Beijing 100875,China;Faculty of Psychology,Beijing Normal University,Beijing 100875,China)
出处
《心理科学进展》
CSSCI
CSCD
北大核心
2021年第9期1696-1710,共15页
Advances in Psychological Science
基金
国家自然科学基金项目(32071091)。
关键词
异常作答
反应时
阈值
残差法
混合模型
aberrant responses
response time
threshold
residual method
mixture model
