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Jan 02, 2025
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SOC 425 - Hierarchical Data Analysis in R Sociology is fundamentally the study of interaction – how individual characteristics and experiences determine and are determined by our engagement with familial, community, economic, political, and cultural realities. In other words, our social realities are deeply determined by the contexts in which we live, work, and play. However, most basic analytic frameworks (such as Ordinary Least Squares regression) are ill-suited to accurately representing associations between characteristics measured at different levels, which makes it difficult to account for the impacts of social context on individual or group outcomes. Hierarchical or Multilevel Linear Regression models (HLMs) allow researchers to simultaneously assess social relationships involving theoretically relevant characteristics across multiple units of analysis. This class will equip students with the tools to understand when and how to apply Hierarchical models in R to better understand how context shapes a range of sociodemographic and economic outcomes.
Prerequisites & Notes: SOC 304; SOC 306; SOC 320. Credits: 5 Grade Mode: Letter
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