The Popperian view has had, and continues to have, a remarkable influence on the development of economics and on what economists do. Examined are the hypothetico-deductive method and the role and nature of empirical testing. (RM)

The notion of multidimensional structure is discussed within the framework of an additive component model of multidimensional scaling, where a configuration is considered to be composed of disjoint subspaces, each one of which reflects variation due to a specific stimulus component. Empirical examples are given. (Author/BW)

The multivariate stochastic processes associated with the Marshall-Olkin multivariate exponential distribution are shown to be able to generate several models of similarity or preference data in the literature. (JKS)

Milligan presented the conditions that are required for a hierarchical clustering strategy to be monotonic, based on a formula by Lance and Williams. The statement of the conditions is improved and shown to provide necessary and sufficient conditions. (Author/GK)

Johnson has shown that the single linkage and complete linkage hierarchical clustering algorithms induce a metric on the data known as the ultrametric. Johnson's proof is extended to four other common clustering algorithms. Two additional methods also produce hierarchical structures which can violate the ultrametric inequality. (Author/CTM)

A revised theorem is presented concerning uniqueness of minimum rank solutions in common factor analysis. (Author)

Various types of finite mixtures of confirmatory factor analysis models are proposed for handling data heterogeneity. Proposed classes of mixture models differ in their unique representations of data heterogeneity, and three sampling schemes for these mixtures are distinguished. Advantages of the Approximate Scoring method are outlined. (SLD)

The Schmid-Leiman (J. Schmid and J. M. Leiman, 1957) decomposition of a hierarchical factor model converts the model to a constrained case of a bifactor model with orthogonal common factors that is equivalent to the hierarchical model. This article discusses the equivalence of the hierarchical and bifactor models. (Author/SLD)

The idea of test consistency is illustrated, with reference to two sets of test scores. A mathematical model is used to explain the relative consistency and relative inconsistency of measurements, and a means of indexing reliability is derived using the model. Practical aspects of estimating reliability are considered. (TJH)

A theorem is developed to show that the Kruskal-Wallis test (W. Kruskal and W. Wallis, 1952) (KWt) can be used validly to test a hypothesis about location under much less restrictive conditions than required by the recently accepted, mathematically correct shift model. The specific null hypothesis for which the KWt can be used validly is…

Demonstrated that the extra-factor phenomenon (the two-dimensional solution produced when linear factor analysis is applied to a set of unfoldable items) arises because the metric unidimensional unfolding model is equivalent to the unidimensional quadratic factor model and the unidimensional quadratic factor model is not distinguishable from the…

Generalized bilinear models are presented for the statistical analysis of two-way arrays. These models combine bilinear models and generalized linear modeling, and yield a family that includes many useful models. A three-step procedure is presented for analyzing data sets by generalized bilinear models. (SLD)

Used simulation to study two different approaches to latent variable interaction modeling with continuous observed variables: (1) a LISREL 8.30 program and (2) data analysis through PRELIS2 and SIMPLIS programs. Results show that parameter estimation was similar but standard errors were different. Discusses differences in ease of implementation.…

Uses examples of hierarchical linear modeling (HLM) at local and national levels to illustrate proper applications of HLM and dummy variable regression. Raises cautions about the circumstances under which hierarchical data do not need HLM. (SLD)

Describes methods for fitting a fuzzy consensus partition to a set of partitions of the same set of objects. Describes and illustrates three models defining median partitions and compares these methods to an alternative approach to obtaining a consensus fuzzy partition. Discusses interesting differences in the results. (SLD)