Friedman Alinda, Kohler Bernd
Department of Psychology, University of Alberta, Edmonton, Canada.
Psychol Methods. 2003 Dec;8(4):468-91. doi: 10.1037/1082-989X.8.4.468.
Bidimensional regression is a method for comparing the degree of resemblance between 2 planar configurations of points and, more generally, for assessing the nature of the geometry (Euclidean and non-Euclidean) between 2-dimensional independent and dependent variables. For example, it can assess the similarity between location estimates from different tasks or participant groups, measure the fidelity between cognitive maps and actual locations, and provide parameters for psychological process models. The authors detail the formal similarity between uni- and bidimensional regression, provide computational methods and a new index of spatial distortion, outline the advantages of bidimensional regression over other techniques, and provide guidelines for its use. The authors conclude by describing substantive areas in psychology for which the method would be appropriate and uniquely illuminating.
二维回归是一种用于比较两个点的平面配置之间相似程度的方法，更广泛地说，是用于评估二维独立变量和因变量之间几何性质（欧几里得和非欧几里得）的方法。例如，它可以评估来自不同任务或参与者组的位置估计之间的相似性，测量认知地图与实际位置之间的逼真度，并为心理过程模型提供参数。作者详细阐述了一维回归和二维回归之间的形式相似性，提供了计算方法和空间扭曲的新指标，概述了二维回归相对于其他技术的优势，并提供了使用指南。作者最后描述了该方法适用且能提供独特启示的心理学实质领域。
