STAT 372
Longitudinal Data Analysis: Modeling Change over Time Spring 2019
Division III Quantative/Formal Reasoning
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This course explores modern statistical methods for drawing scientific inferences from longitudinal data, i.e., data collected repeatedly on experimental units over time. The independence assumption made for most classical statistical methods does not hold with this data structure because we have multiple measurements on each individual. Topics will include linear and generalized linear models for correlated data, including marginal and random effect models, as well as computational issues and methods for fitting these models. We will consider many applications in the social and biological sciences.
The Class: Type: lecture
Limit: 30
Expected: 20
Class#: 3759
Grading: no pass/fail option, no fifth course option
Requirements/Evaluation: evaluation will be based primarily on performance on exams, homework, and a project
Prerequisites: STAT 201 and STAT 346
Enrollment Preferences: junior and senior Statistics majors
Distributions: Division III Quantative/Formal Reasoning
Attributes: PHLH Statistics Courses

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