University of Giessen, Germany.
Br J Math Stat Psychol. 2020 Feb;73(1):164-169. doi: 10.1111/bmsp.12161. Epub 2019 Feb 12.
Although a statistical model might fit well to a large proportion of the individuals of a random sample, some individuals might give 'unusual' responses that are not well explained by the hypothesized model. If individual responses are given as continuous response vectors, M-distances can be used to produce real valued indicators of how well an individual's response vector corresponds to a covariance structure implied by a psychometric model. In this note, we focus on the so-called one-factor model. Two M-distances, d and d , which are sensitive to different aspects of the assumed factor model, have been proposed. While one of the M-distances, d , has been derived based on Bartlett factor scores, in this note we show that the second M-distance, d , can be derived in an analogous fashion based on Thomson factor scores.
虽然统计模型可能很好地适用于随机样本的很大一部分个体,但有些个体的反应可能“异常”,无法很好地用假设的模型来解释。如果个体反应被表示为连续的反应向量,那么 M 距离可以用来产生实数指标,以衡量个体的反应向量与心理测量模型所暗示的协方差结构的吻合程度。在本说明中,我们专注于所谓的单因素模型。已经提出了两种 M 距离,d 和 d ,它们对假设的因子模型的不同方面敏感。虽然其中一种 M 距离,d ,是基于巴特利特因子得分推导出来的,但在本说明中,我们表明,第二种 M 距离,d ,可以类似地基于汤姆森因子得分推导出来。