Temperamental characteristics can be conceptualized as either continuous dimensions or qualitative categories. The distinction concerns the underlying temperamental characteristics rather than the measured variables, which can usually be recorded as either continuous or categorical variables. A finite mixture model captures the categorical view, and we apply such a model here to two sets of longitudinal observations of infants and young children. A measure of predictive efficacy is described for comparing the mixture model with competing models, principally a linear regression analysis. The mixture model performs mildly better than the linear regression model with respect to this measure of fit to the data; however, the primary advantage of the mixture model relative to competing approaches, is that, because it matches our a priori theory, it can be easily used to address improvements and corrections to the theory, and to suggest extensions of the research.
As we approach the end of the 20th century, many serious social problems have arisen on a large scale affecting our world. There is vague anxiety everywhere in modern life, especially among the youth. Presented here are results obtained from an analysis of social anxiety such as the increasing population of aged persons, the drop in the birth rate, the weakening of welfare state, the spread of AIDS, the evil effects of drug abuse, troubles arising out of ethnocentrism, and the rise of Neo-Nazism, increasing domestic violence among young, the abuse of children, rape and other violent acts, etc. The questionnaire method was used to determine the structure toward the items consists of global crisis, and responses to individual questions were subjected to factor analysis. These characteristics and their background are discussed from the viewpoint of psychological considerations.
The purpose of this paper is to propose a new model which combines latent class analysis and the multinomial logit model. Latent classes of this model are introduced to explain and predict choice behavior effectively. Simulation study demonstrates this model as good compromise to deal with individual differences. Finally, this model is applied to the analysis of the real data, and three meaningful latent classes were found to explain consumers' car selection.
The present paper discusses a comparative study of social values between Germany and Japan, based on the data of ALLBUS (1982) and the nationwide survey data collected in Japan in 1991. The main topics are a) desirable quality for a child, b) legal abortion, c) most important aspect of job, d) meaning of Life, e) share received in a social life, f) country's goal, and g) membership in organizations. Results of the survey analysis on these topics show some differences between the two nations. For example, on “desirable quality for a child”, the Germans desire qualities concerned with a child's personal traits while the Japanese desire qualities which would seem to be concerned with interpersonal relationships. The Japanese belong to over twice the number of organizations that Germans do, implying that relationships with others are more important for the Japanese. As for “legal abortion”, the Japanese do not have firm opinions. The Germans tended to consider legal abortion somewhat less acceptable than the Japanese, and show some variations of their opinions on age and religion depending on the content of questions about legal abortion.
This paper concerns with the generation of equivalent path models in the linear structural equation models. Equivalent path models are defined as the set of different path models which give the same value of global fit indices to a data matrix. Therefore, by definition, the data matrix at hand cannot distinguish those models. After deriving some algebraic results, a graphical method to generate a set of equivalent models of a given path matrix is presented. As the result, it is demonstrated that, for most of the four-variable cases, there exists a set of equivalent path models. This implies that the cause-effect terminology used in the interpretation of the result of the data analysis using the linear structural equation models is questionable in most of the cases, unless the causal order is determined prior to the analysis on some theoretic basis.