A0750
Title: Application of the meta-analytic Gaussian network aggregation approach to investigate flourishing across 22 countries
Authors: Michela Zambelli - Università Cattolica del Sacro Cuore of Milan (Italy) [presenting]
Abstract: As a multi-dimensional construct, recent work has begun to explore the interrelatedness among flourishing constituents and their contribution to the achievement and maintenance of individual well-being. Using the national representative survey data from the first wave of the global flourishing study (total N = 202,898), a meta-analytic Gaussian network aggregation (MAGNA) approach was applied using psychonetrics R package to investigate similarity and differences among the reciprocal interrelation of well-being components across 22 countries. MAGNA is based on estimating a Gaussian graphical model by aggregating over multiple datasets, from which a fixed-effect structure and a random-effects structure can be obtained. The MAGNA approach allowed for obtaining a common cross-country network of flourishing and a variance-covariance matrix of random effects that quantify the heterogeneity of edges across countries. It comments, using real data, on the potential of the MAGNA approach to address the need in social science research to aggregate multiple studies to obtain a sufficiently large sample size and increase the reproducibility and reliability of statistical inferences.
