Building Better Blockmodels: A Non-Hierarchical Extension of CONCOR With Applications to Regression Analysis

Cluster analysis has been used by many as a tool for identifying relatively small numbers of categories which represent the salient contrasts within bodies of data. One method which has received widespread use among sociologists in general, and sociometrists in particular, is CONCOR. This paper presents a non-hierarchical extension of the CONCOR algorithm and demonstrates the advantages of this extension with three exemplary bodies of data. One of the bodies of data is then. used as a vehicle for expanding on the information which is customarily derived from cluster, or blockmodel, analyses. Specifically, a means by which the results of blockmodeling may be translated into a regression model is described and demonstrated using these network data

Acute torsion of the gallbladder: a case report

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Perceived economic self‑sufficiency: a countryand generation‑comparative approach

We thank Michael Camasso and Radha Jagannathan as well as Asimina Christoforou, Gerbert Kraaykamp, Fay Makantasi, Tiziana Nazio, Kyriakos Pierrakakis, Jacqueline O’Reilly and Jan van Deth for their contribution to the CUPESSE project (Seventh Framework Programme; Grant Agreement No. 61325). CUPESSE received additional funding from the Mannheim Centre for European Social Research (MZES) and the Field of Focus 4 “Self-Regulation and Regulation: Individuals and Organisations” at Heidelberg University. We further acknowledge helpful comments on this article by two anonymous reviewers. Julian Rossello provided valuable research assistance.Electronic supplementary material The online version of this article (https ://doi.org/10.1057/ s4130 4-018-0186-3) contains supplementary material, which is available to authorized users.Existing datasets provided by statistical agencies (e.g. Eurostat) show that the economic and financial crisis that unfolded in 2008 significantly impacted the lives and livelihoods of young people across Europe. Taking these official statistics as a starting point, the collaborative research project “Cultural Pathways to Economic Self-Sufficiency and Entrepreneurship in Europe” (CUPESSE) generated new survey data on the economic and social situation of young Europeans (18–35 years). The CUPESSE dataset allows for country-comparative assessments of young people’s perceptions about their socio-economic situation. Furthermore, the dataset includes a variety of indicators examining the socio-economic situation of both young adults and their parents. In this data article, we introduce the CUPESSE dataset to political and social scientists in an attempt to spark a debate on the measurements, patterns and mechanisms of intergenerational transmission of economic self-sufficiency as well as its political implications.CUPESSE project (Seventh Framework Programme; Grant Agreement No. 61325