Generalized Structured Component Analysis (GSCA) represents component-based structural equation modeling. Currently, GSCA is geared only for the analysis of quantitative data. In this paper, GSCA is extended to deal with qualitative data through data transformation. In particular, the optimal scaling approach is adopted for data transformation as it can be readily coupled with the GSCA estimation procedure. An alternating least-squares algorithm is developed that involves two phases for estimation of model and data parameters. Two empirical applications are presented to demonstrate the usefulness of the proposed method.
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.
It is well known that health and social factors are closely related. The aim of this study is to examine subjective health through the analysis of cross-national comparative surveys to clarify cultural characteristics of subjective health (self-rated health). I examined countries/areas using the results of our past surveys (Tabkle 1. Yoshino, Nikaido & Fujita, 2009, Behaviormetrica, 36, 2, 89-113). In this analysis, I examined self-rated health symptoms, health satisfaction, life satisfaction, and sense of anxiety as well as other social factors. Multidimensional data analyses of all items on subjective health and on social factors showed a similar pattern between countries/areas. Furthermore, multidimensional scaling for Japanese emigrants and their offsprings and their related countries showed meaningful cultural links of comparison but not so large generational difference between 2-SEI and 3-SEI with respect to health and life satisfactions.
An association analysis of people's environmental consciousness and their pro-environmental behaviors was performed using a statistical survey data set collected in Beijing, Seoul, Taipei and Tokyo, the four largest cities in East Asia, based on random sampling in 2005 and 2006. Although there were remarkable differences in people's attitudes toward environmental issues under the different environmental qualities, economic situations and social institutions in each city, statistical analysis demonstrated that six pro-environmental actions, including “buying eco-good”, “recycling”, “water saving”, “energy saving”, “riding a public transportation” and “buying organic vegetable”, were closely related to people's recognition of environmental changes, their intrinsic values and demographic attributes. The author also found that cultivation of environmental consciousness is an important factor in evoking people's pro-environmental behaviors. Especially, it is necessary to construct an international framework of harmony with regard to environmental issues in which the diversity of environmental consciousness in different social backgrounds in East Asia is taken into account.