Statistics 212 - Statistical Methods III
Monday and Wednesday, 9:30-10:50, Room: DBH 1300
Tuesday, 11:00-11:50, Room: SSL 159
Statistics 211 (Statistical Methods I) or equivalent
This course will provide an introduction to the development and application of statistical methods for analyzing correlated data from experiments and cohort studies. Topics covered include repeated measures ANOVA, linear mixed models, non-linear mixed effects models, and generalized estimating equations. The course will emphasize both theoretical development and application of methods.
Analysis of Longitudinal Data by Diggle, P, Heagerty, P, Liang, KY, and Zeger, S. (2nd edition). Oxford University Press, 2002.
Fitzmaurice G., Laird, L., and Ware J. (2004). Applied Longitudinal Data Analysis, Second Edition. Wiley Series in Probability and Statistics.
McCulloch, C. E., & Neuhaus, J. M. (2001). Generalized linear mixed models. John Wiley & Sons, Ltd.
Verbeke, G., & Molenberghs, G. (2009). Linear mixed models for longitudinal data. Springer Science & Business Media.
McCullagh P. and Nelder, J. (1989). Generalized Linear Models, Second Edition. Chapman & Hall/CRC.
Agresti, A. (2015). Foundation of Linear and Generalized Linear Models, First Edition. Wiley.
There will be a total of 6-8 homework assignments. Assignments will typically be due 1 to 1.5 weeks from the day they are handed out.
Tentatively scheduled for Wednesday, May 16th. The exam will be in-class (closed-book, closed-note), and will cover material through the May 9th lecture.
The final exam is scheduled for Wednesday, June 13th, 8:00-10:00am. The final exam will be take-home and will consist of two portions. The first portion of the exam will consist of short answer questions similar to a comprehensive homework assignment. The second portion of the exam will be a complete statistical analysis and report pertaining to a particular scientific question. The final exam will be handed out on Monday, June 4th and due on Wednesday, June 13th by 10:00am.
All students are expected to abide by the UCI academic honesty policy. Among other things, this means that copied homework solutions will receive no credit in the course. I encourage students to study and work together on homework. However, the work that is handed in should reflect only that student’s work. That is, obtaining help from other students in order to learn the METHODS of solution is allowed, but copying another student’s answer or a past course key is NOT.