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BST 226 - Applied Longitudinal Analysis or return to Course Catalog Search

190043 – Section 1   

SchoolDepartmentFaculty
Harvard T.H. Chan School of Public HealthBiostatisticsGarrett Fitzmaurice
TermDay and TimeLocation
Spring (Full Term) 2018  (show academic calendar)TuTh   2:00 p.m. - 3:30 p.m.Kresge G1 (HSPH)
Credits
5  (show credit conversion for other schools)
Credit Level
Graduate

Description
This course covers modern methods for the analysis of repeated measures, correlated outcomes and longitudinal data, including the unbalanced and incomplete data sets characteristic of biomedical research. Topics include an introduction to the analysis of correlated data, analysis of response profiles, fitting parametric curves, covariance pattern models, random effects and growth curve models, and generalized linear models for longitudinal data, including generalized estimating equations (GEE) and generalized linear mixed effects models (GLMMs).Course Activities: Homework assignments will focus on data analysis in SAS using PROC GLM, PROC MIXED, PROC GENMOD, and PROC GLIMMIX.Course Note: Lab or section times will be announced at first meeting.Course Prerequisite(s): BST210 or BST213 or BST232 or BST260 or PHS2000A.Formerly BIO226

Prerequisite(s)
Prerequisite: BST210 or BST213 or BST232 or BST260 or PHS2000A

 
Cross Registration
Eligible for cross-registration
With permission of instructor/subject to availability

MIT students please cross register from MIT's Add/Drop application.

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