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By the end of this unit you will be able to:

  • Comprehend the basic idea of multilevel modelling
  • Explain why multilevel modelling is useful when linking macro (group level aggregate) and micro (individual survey) data.
  • Present the kinds of substantive research questions that can be asked when linking macro and micro data in a multilevel model
  • Outline software that permits multilevel models to be fitted.
  • Explain how this software may be used to fit a multilevel model with a binary outcome.
  • Give an example of multilevel modelling a binary outcome with micro data from the European Social Survey (ESS)
  • Give an example of linking micro and macro data in the multilevel model framework by combining the ESS micro data with country-level macro data from Eurostat New Cronos, for long term unemployment.
  • Outline the various multilevel models in this context -both substantively and theoretically
  • Explain how interactions between aggregate and individual level measures work in these models and why they might answer important substantive research questions.
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The University of Manchester; Mimas; ESRC; RDI

Countries and Citizens: Unit 5 Multilevel modelling using macro and micro data by Mark Tranmer, Cathie Marsh Centre for Census and Survey Research is licensed under a Creative Commons Attribution-Non-Commercial-Share Alike 2.0 UK: England & Wales Licence.