Alternating Least Squares Optimal Scaling: Analysis of Nonmetric Data in Marketing Research
讨论了一种基于交替最小二乘最优尺度的方法，用于分析营销研究中的度量与非度量数据，扩展了线性模型（如方差分析、回归）的灵活性，适用于名义、序数或区间水平的数据。
The authors discuss and illustrate the advantages and limitations of a family of new approaches to the analysis of metric and nonmetric data in marketing research. The general method, which is based on alternating least squares optimal scaling procedures, extends the analytical flexibility of the general linear model procedures (ANOVA, regression, canonical correlation, discriminant analysis, etc.) to situations in which the data (1) are measured at any mixture of the nominal, ordinal, or interval levels and (2) are derived from either a discrete or continuous distribution. The relationship of these procedures to traditional linear models and to other nonmetric approaches (such as multidimensional scaling and conjoint analysis) is reviewed.