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140.607.11 MULTILEVEL MODELS

Department: Biostatistics
Term: Summer Inst. term
Credits: 2 credits
Academic Year: 2012 - 2013
Course Instructor:
  • Elizabeth Colantuoni
Description:

Gives an overview of "multilevel statistical models" and their application in public health and biomedical research. Multilevel models are regression models in which the predictor and outcome variables can occur at multiple levels of aggregation: for example, at the personal, family, neighborhood, community and regional levels. They are used to ask questions about the influence of factors at different levels and about their interactions. Multilevel models also account for clustering of outcomes and measurement error in the predictor variables. Students focus on the main ideas and on examples of multi-level models from public health research. Students learn to formulate their substantive questions in terms of a multilevel model, to fit multilevel models using Stata during laboratory sessions and to interpret the results.

Learning Objective(s):
Upon successfully completing this course, students will be able to:
Prepare graphical and tabular displays of multilevel data that effectively communicate the patterns of scientific interests
Conduct statistical analyses of clustered data by use of multilevel models
Interpret parameters of multilevel statistical models
Fit multilevel models by use of statistical software packages

Methods of Assessment: Final exam
Location: East Baltimore
Class Times:
  • Mon 07/02/2012 - Fri 07/06/2012
  • Monday 1:30 - 5:00
  • Tuesday 1:30 - 5:00
  • Wednesday 1:30 - 5:00
  • Thursday 1:30 - 5:00
  • Friday 1:30 - 5:00
Enrollment Minimum: 10
Instructor Consent: No consent required
Prerequisite:

Previous experience with regression analysis is required.

Auditors Allowed: No
Grading Restriction: Letter Grade or Pass/Fail