VHM 881: Statistical Analysis of Generalized, Linear, and Mixed Models -
Fall Semester 2009
Welcome to the homepage of the directed studies course VHM 881 offered in the fall semester of 2004, at the
Department of Health Management, Atlantic Veterinary College, last
updated 15/12-2009.
Course outline
This graduate course is intended for students with a background in statistics
corresponding to at least BSc level. It covers the foundations of statistical
models for continuous and discrete data involving random effects, so-called
"mixed models", e.g. corresponding to a hierarchical data structure (e.g.
animals in farms). The student will learn the mathematical and statistical
theory involved in analysing such models, and apply the methodology to selected
sample datasets using statistical software (R program). In contrast to applied
courses (such as "Introduction to Multilevel Modelling", offered within the
framework of VHM 831), the course will give the student the theoretical tools to
read statistical papers on the subject and to study and implement non-standard
extensions of the procedures.
- Course material:
- MSN: McCullogh CE, Searle SR, Neuhaus JM (2008), Generalized, Linear, and Mixed Models, 2nd ed, Wiley, 424pp.
- VR: Venables WN, Ripley BD (2002), Modern Applied Statistics with S, 4th ed., Springer, 495pp.
- PB: Pinheiro JC & Bates DM (2000), Mixed-Effects Models in S and S-PLUS, Springer, 528pp.
- BC: Breslow NE & Clayton DG (1993), Approximate inference in generalized linear mixed models, Journal of the American Statistical Association 88, 9-25.
- WO: Wolfinger R, O'Connell M (1993), Generalized linear mixed models: a pseudo-likelihood approach, Journal of Statistical Computation and Simulation 48, 233-243.
- RSP: Rabe-Hesketh S, Skrondal A & Pickles A (2002), Reliable estimation of generalised mixed models using adaptive quadrature, The Stata Journal 2, 1-21.
- SR: Skrondal A, Rabe-Hesketh S (2009), Prediction in multilevel generalized linear models, Journal of the Royal Statistical Society, A 172, 359-387.
- VSR: Venables WN, Smith DM, R Development Core Team (2009): An
Introduction to R, version 2.9.2.
- Course schedule:
tutorial session: Wednesdays 3-4pm, lab session: Mondays 9-11am (except for Fridays 9-11am when the
Monday is a holiday); commencing September 2 and 4, for tutorial and lab sessions, respectively.
- Assignments and exam:
Schedule
| Session | Date | Topics | Exercises
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| 1 | Sep 2 | Introduction to course and R software; MSN:1 | MSN: 1.1, 1.2, 1.4(b), 1.6
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| 2 | Sep 9 | One-way classification mixed models; MSN:2 | MSN: 2.3, 2.4, 2.10, 2.11, 2.14, VSR: Ch.1, App.A
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| 3 | Sep 16 | Single-predictor mixed models; MSN:3 | MSN: 3.2, 3.12, 3.13, Example 3.1, VSR: Ch.2-4
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| 4 | Sep 23 | Linear models; MSN:4 | MSN: 4.10, 4.12, 4.18, Example 4.7, VSR: Ch.5
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| 5 | Sep 30 | Generalized linear models; MSN:5 | MSN:5.2,5.9,5.10, Section 5.6, VSR: Ch.6-8
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| 6 | Oct 7 | Linear (generalized) model analysis in R; VR:6-7 + PB:4.1 | VR:6.2,7.6, VR: Extra for Chapter 6, , VSR: Ch.11
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| 7 | Oct 21 | Linear mixed models; MSN:6 | MSN:6.1,6.4,6.5,6.6,6.10(a-c)
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| 8 | Oct 28 | Linear mixed models in R; PB:1+4, VR: 10.1-2; MSN: 14.2 | PB:1.1(dataset),1.2,1.3
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| 9 | Nov 4 | Generalized linear mixed models; MSN:7, BC | MSN:7.3,7.4,7.7; PB:4.3
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| 10 | Nov 11 | Generalized linear mixed modelling in SAS and R; WO, VR:10.4-5; MSN:14.3-4 | MSN:14.2,14.3,14.4,14.6, VR: Extra for Chapter 10
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| 11 | Nov 18 | Departures from model assumptions; MSN:12 | MSN:12.2,12.3,12.7,12.9
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| 12 | Nov 25 | Prediction for mixed models; MSN:13, SR | MSN:13.2,13.6
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| 13 | Dec 9 | Course wrap-up |
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| 14 | Dec 14 | Student seminar |
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Other information
Contact
Henrik Stryhn, Department of Health Management, Atlantic Veterinary College,
room 417S, phone: (902) 894-2847, fax: (902) 566-0823, e-mail: hstryhn@upei.ca.
Henrik Stryhn
(hstryhn@upei.ca)