This paper presents a comparison of attitudes toward social unrest among German and Japanese university students. The method employed is that of the questionnaire by Guttman's facet design. Both youth among the two nations, the main social unrest problem is that of environmental pollution, and politico-economic crisis. The key point of those crises is the problem of the organizing crimes. We can guess that this problem will be a common crime throughout the world in the near future, maybe in the next century. And both youth seemed to be quiet on surface, but they have many serious problems in their minds in spite of their optimistic outlook. These problems are discussed from a social psychological point of view.
A factor-analytic model for discrete variables which represent frequencies is developed. The model assumes that the frequencies are generated by the Poisson distribution, in which the logarithm of the parameter of the distribution takes a similar form to the factor-analysis model for continuous variables. The latent variables in the model, which correspond to common factors in factor analysis, are assumed to have independent distributions with fixed parameters or a multivariate normal distribution with unknown correlations. The individual factor scores are integrated out from the model and factor-loadings in the sense of the generalized linear model are obtained by the marginal maximum likelihood method. Numerical examples of non-verbal intelligence tests are given.
In this paper a social quantum theory is proposed for the analysis of dynamic changes of responses in public opinion surveys. After a summary of previous findings of panel survey data, mathematical propositions are presented for an explanation of the survey response patterns called “small integral ratios” : response percentage ratios of two categorical items tend to converge to certain stable fixed points represented by ratios of pairs of small integers. Then, for the study of panel survey data and the small integral ratios from a viewpoint of quantum theory, categorical scaling of survey responses on Schrödinger's wave equation is tentatively constructed and it is statistically tested on data previously collected. Finally, some comments and suggestions are presented for future research.
This article illustrates that careful attention must be paid to “I do not know” (DK) answers when modeling the profiles and political inclinations of the Japanese independent voters. The DK answers, concentrated on answers to the questions regarding the support for the current cabinet and political ideology, are treated as missing because there is no valid reason to treat them as one separate category. We perform logistic regression analysis of binary response whether the interviewee has a political party to support or not on several political and economic explanatory variables, within which the EM algorithm is implemented. This enables us to incorporate the cases with missing-values into the analysis. We found that missing-value problem could not be ignored in the sense that marginally significant or insignificant explanatory variables can easily turn otherwise when the same model is fitted only for the data with no missing-values.
Association models have been presented for the analysis of singly-ordered contingency tables. The models contain some parameters regarded as category scores, and offer some additional insight into the meaning of these scores. We propose an association model with location and dispersion scores for the analysis of association in crossclassifications having singly-ordered response categories. Some issues of interest in this article are (i) two-dimensional graphical displays of parameter estimates and assigned scores, (ii) tests for homogeneity of row effects in the association model, and (iii) Monte Carlo simulations conducted to investigate the accuracy of the chi-square approximation to the null distribution and the power based on the proposed method. We show that the proposed method improves the power in testing for homogeneity of conditional distributions within rows under certain alternatives, comparing with other methods.
The attraction among a group of subjects was predicted by a procedure which had been originally introduced to predict the amount of purchase of a brand. The procedure, which is based on two multidimensional scaling methods ; INDSCAL and PREFMAP, was applied to friendship tie data among members of a group of 17 students collected once a week for 16 weeks (Newcomb, 1961 ; Nordlie, 1958). Three subjects, who had received relatively unstable and dissimilar attractions among the 17 subjects, were selected. The attraction from the 17 subjects to the three subjects was analyzed by the procedure. The 17 subjects were cluster analyzed using the data at weeks 0 through 8, and were grouped into three clusters. The attraction from each of the three clusters to the three subjects at weeks 0 through 8 were analyzed to predict the attraction at weeks 9 through 15. The predicted attraction was compared with the actual attraction at weeks 10 through 15 (data at week 9 were missing). The comparison shows that five of the nine root mean squares of discrepancy between the predicted and actual attractions were smaller than unit rank, and that the prediction was successful.