Yuan Ke-Hai, Fung Wing Kam, Reise Steven P
Department of Psychology, University of Notre Dame, USA.
Br J Math Stat Psychol. 2004 May;57(Pt 1):151-65. doi: 10.1348/000711004849231.
Unidimensionality is the hallmark psychometric feature of a well-constructed measurement scale. However, in determining the degree to which a set of items form a unidimensional scale, aberrant item response patterns may distort our investigations. For example, aberrant response patterns may adversely impact interitem covariances which, in turn, can distort estimates of a scale's dimensionality and reliability. In this study, we investigate and compare the utility of three Mahalanobis distance (M-distance) measures in identifying and downweighting aberrant item response patterns. Our findings indicated that a residual-based M-distance measure had the best properties. Specifically, response patterns having greater residual-based M-distances were responsible for observed violations of unidimensionality. When these response patterns were properly downweighted according to this M-distance, the data fitted a one-factor model better and scale reliability increased. The procedures are illustrated using three real data sets.
单维性是一个构建良好的测量量表的标志性心理测量特征。然而,在确定一组项目形成单维量表的程度时,异常的项目反应模式可能会扭曲我们的调查。例如,异常的反应模式可能会对项目间协方差产生不利影响,进而可能会扭曲量表维度和信度的估计。在本研究中,我们调查并比较了三种马氏距离(M距离)测量方法在识别和降低异常项目反应模式权重方面的效用。我们的研究结果表明,基于残差的M距离测量方法具有最佳特性。具体而言,基于残差的M距离较大的反应模式是观察到的违反单维性的原因。当根据这种M距离对这些反应模式进行适当加权时,数据能更好地拟合单因素模型,量表信度也会提高。使用三个真实数据集对这些程序进行了说明。