Predictors and outcomes of social network compositions: A compositional structural equation modeling approach |
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Authors: | Tina Kogovšek Germà Coenders Valentina Hlebec |
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Institution: | 1. University of Ljubljana, Faculty of Arts, Ašker?eva 2 and Faculty of Social Sciences, Kardeljeva pl. 5, 1000 Ljubljana, Slovenia;2. University of Girona, Department of Economics, Faculty Building of Economics and Business, Campus Montilivi, 17071 Girona, Spain;3. University of Ljubljana, Faculty of Social Sciences, Kardeljeva pl. 5, 1000 Ljubljana, Slovenia |
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Abstract: | Proportions of a total, including social network compositions (proportions of partner, family, friends, etc.) lie in a restricted space, which challenges statistical analysis. Network compositions can be both dependent and explanatory variables and are usually measured with error by survey instruments. Structural equation models make it possible to correct measurement error bias. Coenders et al. (2011) fitted a factor analysis model to transformed network compositions. In this article, we use another transformation called an isometric log-ratio and we extend the model to include predictors and outcomes. The findings and hypotheses in the literature can be reformulated with isometric log-ratios in a more interpretable manner. For instance, we find relationships of gender with partner support, of education and extraversion with friend support, and of family support with tie multiplexity and closeness. |
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Keywords: | Network composition Structural equation model Measurement error Log-ratio transformation Compositional data Social support |
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