Spring 2014    PH1918    Methods for correlated data

Course instructors:

Yong Chen



This course presents extensions of general and generalized linear models to longitudinal and correlated outcome data with special emphasis on clinical, epidemiologic, and public health applications. Major topics include generalized linear mixed linear models (GLMM) for continuous, binomial, and count data; maximum likelihood estimation; generalized estimating equations (GEE); current general and specialized software applicable to these methods; and readings from current statistical literature. Each student will be required to participate in 4 labs and complete associated problem sets. Software will include Stata.



1. Diggle, P,  Heagerty, P, Liang, K-Y and Zeger, S. (2013). Analysis of Longitudinal Data (Second Edition). Oxford University Press. ISBN-10: 0198524846.

2. Fitzmaurice GM, Laird NM, Ware JH.  Applied Longitudinal Analysis.  Second Edition. New York: Wiley; 2011.  ISBN: 978-0-470-38027-7. Hardcover  740 pages; August 2011 

3. Singer JD, Willett JB.   Applied Longitudinal Analysis.    New York: Oxford 2003.


Graphics texts: 

Mitchell MN.   A Visual Guide to Stata Graphics.  3rd Edition.  College Station, TX: Stata Press; 2012.

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