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Stats, Volume 7, Issue 1
March 2024 - 20 articles
Cover Story: Social and behavioral scientists use structural equation models (SEMs) as mathematical representations of complex theories involving multivariate data. Sophisticated sampling designs can yield dependencies that complicate standard SEMs, requiring more advanced estimation methods. Round-robin designs have a social-network structure, in which every member of a group is potentially linked to every other member of the same group. This yields dyadic data, in which the same variable is measured for each member of a pair in response to (or about) the other member of the pair. Every person is a member of several pairs within the network. This paper demonstrates a method to account for this complexity in the first step to estimate SEM parameters. View this paper
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Stats - ISSN 2571-905X