Causal inference in collaboration networks using propensity score methods

Abstract

Using panel data of school-class networks of 11–13-year-old students, this study investigates effects of schoolwork collaboration-networks on grades and school-related well-being. It suggests propensity score weighting-regression as a method of causal inference for data collected in social contexts, and in studies analyzing node-attributes as outcomes of interest. It will argued that this alternative approach is useful when stochastic actor-based models (SAOMs) show convergence problems in sparse networks. Three methods of causal analysis dealing with the problems of endogeneity bias and interference between observations will be discussed in this study: first, SAOMs for the co-evolution of networks and behavior/attitudes will be estimated, but this results in a systematic loss of data. Second, propensity score matching compares treated cases with untreated nearest neighbors. However, the stable-unit-treatment-value assumption (SUTVA) requires that the analysis controls for network embeddedness in the final analysis. This is possible by using propensity score weighting-regression, which is a flexible approach to capture treatment diffusion via multiplex networks.

Selection homophily and peer influence for adolescents’ smoking and vaping norms and outcomes in high and middle-income settings

“…Estimates and SEs for each effect parameter in the SIENA models for individual schools were then combined in a metaanalysis, using the multilevel network analysis method of Snijders and Baerveldt (2003). Previous studies using SIENA modeling to investigate the co-evolution of network ties and smoking behavior, and more recently published Stochastic Actor-Oriented Models have used similar meta-analytic procedures to combine estimates across different networks (Block, 2018;Hooijsma et al, 2020;la Roi et al, 2020;Leszczensky and Pink, 2020;Mercken et al, 2009Mercken et al, , 2012Windzio, 2021;Zhang et al, 2020). For each effect, the overall null hypothesis that the effect was 0 in all schools was tested using Fisher's combination of one-sided tests procedure with two onesided tests (Fisher, 1925;Hedges and Olkin, 1985).…”