2009 年 37 巻 1 号 p. 15-32
The traditional quantification procedure (e.g., dual scaling, correspondence analysis) is extended in order to tap into information which is typically ignored. Noting that the traditional symmetric scaling yields a visual image of distorted data structure and recalling that the widely used practice of looking at data in reduced space may also miss capturing rare but key-information in total space, a method, called total information analysis (TIA), is proposed to subject not only within-set but also between-set relations in total space. Numerical examples are used to explain why TIA offers partial solutions to some theoretical problems inherent in the current practice of multidimensional quantification analysis.
