The paper presents to Czech social scientists an introductory review of the concept of equivalence and the method of blockmodeling in social network analysis (SNA). After introducing the central concepts of SNA such as node and tie, along with their basic metrics such as centrality and cohesion, I present the concepts of role and position. These are treated by SNA as clusters of nodes with similar ties, something I juxtapose to algorithms to identify cohesive subgroups of nodes. Subsequently, I define and compare the two most frequently applied types of equivalence - structural, which is strict but broadly applicable, and regular, which is more liberal but has limited uses. Structural equivalence builds on a strict definition of similarity of ties, treating as equivalent only such nodes that have the same ties to the same other nodes. Regular equivalence works with looser criteria and better corresponds with both the theoretical and the intuitive notions of role; this, however, is outweighed by the absence of a unique regular-equivalent solution within a network and by the difficulty to process networks with undirected ties. Regular-equivalent nodes are such that have ties to other mutually equivalent nodes. I present examples to demonstrate the differences between both definitions. In the following section, I discuss measurement of similarity between the different nodes’ profiles of ties (e.g., correlation and Euclidean distance) and possible uses of the standard statistical methods of cluster analysis and multidimensional scaling to detect equivalent classes of nodes within networks. After pointing to the weaknesses of these techniques in network data analysis, I present blockmodeling as a method designed specifically to identify roles and positions within networks. Ischematize the blockmodeling procedure and present its basic terms before comparing classic inductive blockmodeling, which is primarily fit for the purposes of exploration and network reduction, with deductive generalized blockmodeling, which is applicable in testing hypotheses about basic structural characteristics of a network. I bring attention to the strengths and weaknesses of both approaches. Relatedly, I present an application of blockmodeling especially for the purposes of simplified network representation, comparing structural patterns across networks, and testing structural theories. In the following section, I demonstrate specific blockmodeling algorithms based on both structural equivalence (CONCOR and Tabu Search optimization) and regular equivalence (REGE and Tabu Search optimization). Then I verify the adequacy of their resulting assignment of positions to nodes using eta coefficient, Q modularity and correlation of the ideal blocked and the empirical adjacency matrices. In the concluding section, I demonstrate the entire blockmodeling procedure on an empirical case of a small network with undirected ties using the UCINET software tool, including interpretation of results. Finally, I reflect the contemporary position of blockmodeling among leading research approaches in SNA, referring to other empirically oriented studies that demonstrate the broad applicability and utility of position analysis., Tomáš Diviák., and Obsahuje použitou literaturu a poznámky
Dietary composition and metabolism of fatty acids (FA) influence insulin resistance, atherogenic dyslipidemia and other components of the metabolic syndrome (MS). It is known that patients with MS exhibit a heterogeneous phenotype; however, the relationships of individual FA to MS components have not yet been consistently studied. We examined the plasma phosphatidylcholine FA composition of 166 individuals (68F/98M) with MS and of 188 (87F/101M) controls. Cluster analysis of FA divided the groups into two clusters. In cluster 1, there were 65.7 % of MS patients and 37.8 % of controls, cluster 2 contained 34.3 % of patients and 62.2 % of controls (P<0.001). Those with MS within cluster 1 (MS1) differed from individuals with MS in cluster 2 (MS2) by concentrations of glucose (P<0.05), NEFA (P<0.001), HOMA-IR (P<0.05), and levels of conjugated dienes in LDL (P<0.05). The FA composition in MS1 group differed from MS2 by higher contents of palmitoleic (+30 %), γ-linolenic (+22 %), dihomo-γ-linolenic (+9 %) acids and by a lower content of linoleic acid (–25 %) (all P<0.01). These FA patterns are supposed to be connected with the progression and/or impaired biochemical measures of MS (lipolysis, oxidative stress, dysglycidemia, and insulin resistance)., A. Žák, M. burda, M. Vecka, M. Zeman, E. Tvrzická, B. Staňková., and Obsahuje bibliografii
Monitoring of groundwater quality in Bareilly district, Uttar Pradesh, India, was performed at 10 different sites during the years 2005-2006. Obtained quality parameters were treated using principal component analysis (PCA) and cluster analysis (CA). The study shows usefulness of multivariate statistical techniques for evaluation and interpretation of groundwater quality data sets. and V letech 2005-2006 byla na deseti odběrných místech v regionu Bareilly, Uttar Pradesh, Indie sledována kvalita podzemní vody. Zjištěné kvalitativní parametry byly zpracovány pomocí analýzy hlavního prvku (PCA) a pomocí shlukové analýzy (CA). Studie dokládá vhodnost multivariačních statistických metod pro vyhodnocení a interpretaci změřených výsledků.