In pharmacokinetics, compartment models often play an important role in the description of the concentration of the drug in the blood over time after its administration to a subject. In the inference in the compartment models in pharmacokinetics, unlike that of the usual nonlinear regression models, parameterizations with respect to the parameters related to pharmacokinetic indices are frequently applied, for some reasons of the constraint that the parameter takes only the positive value, facilitation of the compartment models, or interpretation of the relationships between the parameters and the demographic or physiological individual attributes. However, in practice no attention is paid to checking if the utilized parameterization is valid. In this article, the relative curvature measure that enables us to assess the intrinsic and parameter-effects nonlinearity in the model is applied for checking it from the latter nonlinearity. From a viewpoint of the relative curvature measure, we reconsider several well-known examples and demonstrate the parameterization checking.
The generalized partial correlation is defined as a correlation between two variables, where the linear effects of common and unique third variables are partialed out from the two variables. The generalized partial correlation includes simple, partial, part/semipartial and bipartial correlations as special cases. The Edgeworth expansion of the distribution of the standardized sample coefficient for the generalized partial correlation is obtained up to order O(1/n) under nonnormality. Also asymptotic expansions of the distribution of the Studentized estimator are obtained using the Edgeworth expansion, Cornish-Fisher expansion and Hall's method with variable transformation. As extensions, the results of multivariate cases or generalized partial set-correlations are given.
The problem considered in the present paper is how to cluster data of nominal measurement level, where the categories of the variables are equivalent (the variables are replications of each other). One suitable technique to obtain such a clustering is latent class analysis (LCA) with equality restrictions on the conditional probabilities. As an alternative, a less well known technique is introduced: GROUPALS. This is an algorithm for the simultaneous scaling (by multiple correspondence analysis) and clustering of categorical variables. Equality restrictions on the category quantifications were incorporated in the algorithm, to account for equivalent categories. In two simulation studies, the clustering performance was assessed by measuring the recovery of true cluster membership of the individuals. The effect of several systematically varied data features was studied. Restricted LCA obtained good to excellent cluster recovery results. Restricted GROUPALS approximated this optimal performance reasonably well, except when underlying classes were very different in size.
A perfect Guttman scale is rarely found in real data. Pairwise dominance relations between items to be scaled, however, often meet the conditions for less simple orders, such as strict partial orders, interval orders, and semiorders. Examples are thus provided for an extension of the Guttman scale to less simple orders in the framework of ordinal theory, or more specifically, the theory of representations with thresholds. The study is methodologically based on ordering theory. Three illustrative constructions of less simple orders demonstrate that they much more strongly account for real data than do Guttman scales, and that some uniqueness in scale values and thresholds is found in semiorders and interval orders.
Does globalization have a positive or negative impact on democracy? One reason this problem has gone unsolved is found in the fact that most studies to date have not made systematic use of empirical data to test propositions concerning the relationship between globalization and democracy. While there have been studies that have made a pioneering systematic contribution through the use of macroeconomic and other aggregate statistics, this article empirically examines whether globalization enhances or constrains democracy by using cross-national survey data collected in 17 countries (the Asia-Europe Survey). Our empirical testing has shown that globalization tends to be positively correlated to democratic activism at the individual level, suggesting the possibility that experiences of globalization strengthen democracy.