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dime and netreg: Interactive network graphs of marginal effects

Author

Listed:
  • Cristina Calvo López

    (National University of Distance Education (UNED))

  • Modesto Escobar

    (Universidad de Salamanca)

Abstract

Graphs are widely used to represent social structures and to study relationships between variables. This presentation proposes an approach that extends their analytical potential by combining regression modeling with interactive network visualization. The method fits generalized linear models (including multinomial models) and their mixed-effects extensions, then identifies the categories whose predicted proportions or means differ significantly from the weighted population mean. The resulting graphs highlight these categories, making the most relevant effects immediately visible. Interactivity adds a further layer: users can filter nodes by size or attributes and explore the most central nodes and strongest links within the network. We present two new commands, dime and netreg, that compute marginal effects from the fitted models and generate the interactive graphs. Their use is illustrated with a variety of applied examples drawn from statistical studies.

Suggested Citation

Handle: RePEc:boc:spai26:05
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