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BST 210 - Applied Regression Analysis or return to Course Catalog Search

190025 – Section 1   

SchoolDepartmentFaculty
Harvard T.H. Chan School of Public HealthBiostatisticsDavid Wypij
TermDay and TimeLocation
Fall (Full Semester) 2017  (show academic calendar)MW   8:00 a.m. - 9:30 a.m.Kresge G2 (HSPH)
Credits
5  (show credit conversion for other schools)
Credit Level
Graduate

Description
Topics include model interpretation, model building, and model assessment for linear regression with continuous outcomes, logistic regression with binary outcomes, and proportional hazards regression with survival time outcomes. Specific topics include regression diagnostics, confounding and effect modification, goodness of fit, data transformations, splines and additive models, ordinal, multinomial, and conditional logistic regression, generalized linear models, overdispersion, Poisson regression for rate outcomes, hazard functions, and missing data. The course will provide students with the skills necessary to perform regression analyses and to critically interpret statistical issues related to regression applications in the public health literature.Prerequisites: ID201 or BST201 or (BST202 and BST203) or (BST206 and (BST207 or BST208)) or permission of instructor

Prerequisite(s)
HSPH: BST210

 
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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