University of California, Berkeley 5 credits Berkeley School of Education
The course introduces hierarchical linear and generalized linear models for longitudinal or clustered data. Such models are important in education research where longitudinal development such as learning is of interest and where students are clustered in classes or schools. Other examples of clustering are people nested in neighborhoods, hospitals, or firms. Students will practice formulating and estimating hierarchical models using either educational data sets provided or their own data sets.
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