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ST 732 Longitudinal Data Analysis
Introduction to modeling longitudinal data; Population-averaged vs. subject-specific modeling; Classical repeated measures analysis of variance methods and drawbacks; Review of estimating equations; Population-averaged linear models; Linear mixed effects models; Maximum likelihood, restricted maximum likelihood, and large sample theory; Review of nonlinear and generalized linear regression models; Population-averaged models and generalized estimating equations; Nonlinear and generalized linear mixed effects models; Implications of missing data; Advanced topics (including Bayesian framework, complex nonlinear models, multi-level hierarchical models, relaxing assumptions on random effects in mixed effects models, among others). Implementation in SAS and R.
Typically offered in Spring only
Statistics (PhD)
/graduate/sciences/statistics/statistics-phd/
1 Unless student has taken ST聽542 Statistical Practice 2 A 500-level or 700-level course in either statistics or another department with material relevant to the student鈥檚 plan of work. Examples include ST聽520 , ST聽531 , ST聽533 , ST聽534 , ST聽537 , ST聽540 , ST聽544 , ST聽546 / MA聽546 , ST聽563 , ST聽721 ,聽 厂罢听732 , ST聽733 , ST聽740 , ST聽745 , ST聽746 , ST聽747 / MA聽747 , and聽 ST聽790 3 Additional courses may include聽 ST聽801 ,聽 ST聽895 聽and courses taken from a Master of Statistics or Master of Science in Statistics degree at NCSU.