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University of Oregon, College of Education Workshop on Multilevel Models |
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This
workshop will provide an introduction to
multilevel modeling. Many social and
natural phenomena have a nested or clustered organization that results
in data with
dependencies associated with group or cluster
membership. Hierarchical
Linear Models (HLM) provide a method for correctly analyzing such data
as well
as a means to study relationships that cross levels. Workshop
participants will
learn foundational principles and concepts in HLM and will have
hands-on
practice using software to apply and interpret basic models. The workshop will cover multilevel data
structures, intraclass correlation, model building, centering, model
testing,
fixed and random effects, two and three level models, longitudinal
growth models,
statistical power and design planning, and the use of HLM in cluster
randomized
trials.
Please direct any questions to Joe Stevens at stevensj@uoregon.edu. Before the workshop, participants should:
Hox, J. (1995). Multilevel Analysis, Read chapters 1 and 2. Raudenbush & Bryk, 1986, Sociology of Education, available at: http://www.uoregon.edu/~stevensj/HLM/raudenbush.pdf Willms & Raudenbush (1989). Longitudinal HLM study of school effects, available at: http://www.uoregon.edu/%7Estevensj/AofC/willms&raudenbush.pdf
Raudenbush, et al. (2007). Strategies for improving precision. Educational Evaluation and Policy Analysis. Hedges & Hedberg (2007). Intra-class correlation values for planning. Educational Evaluation and Policy Analysis.
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