VHM 802, Advanced Veterinary Biostatistics (e-mail 4/1-2021)

Announcement of the Biostats VHM 802 course at AVC (UPEI)

Please find below an outline of the course VHM-8020-1: Advanced Veterinary Biostatistics 
for the Winter Semester 2021. Registration for the course at the Registrar's Office 
takes place through the myUPEI portal. For further information, contact the course lecturer, 
or consult the course homepage (at the bottom of this message) with the most recent and 
detailed information, including a full (tentative) schedule.

The course will be run in part jointly with VHM 8120: Epidemiology II
(Instructor: Dr. Javier Sanchez). Students may take VHM 802 separately
(3 credits) or in combination with VHM 812 (taken simultaneously or in a
previous year, 2 credits).

This year the course will include a substantial component on multivariate analysis, while 
retaining key parts of experimental design as well as the regression parts shared with 
the VHM 812 course. For any inquiries about the course, contact the course lecturer:

Henrik Stryhn,
Department of Health Management, AVC
office: 412S
phone: (902) 894-2847
e-mail: hstryhn@upei.ca

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Biostatistics VHM 802 Course - Winter Semester 2021

Preliminary schedule:
- time: January 11 - April 19; first session January 12, 1-3pm,
- lectures etc. joint with VHM 812:
  mostly Tuesdays 1-3pm and Fridays 9-11am, 12/1-12/2 and 26/3-9/4,
- lectures for VHM 802 only:
  asynchronous video lectures on Thursdays, 18/2-15/4 (excl 1/4),
- labs for VHM 802 only: Mondays 1-4pm in AVC 218S (and streamed), 22/2-19/4.

Course format:
Weekly lectures reviewing the theory and working through examples, supplemented by weekly 
lab sessions containing tutorials of statistical software, discussions of lectures, and 
individual work on statistical analysis using computers. In weeks taught jointly with VHM 812, 
the course typically has two lecture/review online sessions, see detailed schedule.

An applied course project is anticipated for each student, based on the
student's own data or literature data relevant to the student's research.

Textbook:
(1) Chapters 14-16 of Dohoo, Martin and Stryhn: Veterinary
Epidemiological Research; students not taking the VHM 812 course will be
given chapter handouts.
(2) Gary Oehlert: A first Course in Design and Analysis of Experiments,
2000, W.H. Freeman, ISBN 0716735105. The text is out of print, but can
be downloaded for free at http://www.stat.umn.edu/~gary/.
(3) Bryan Manly and Jorge Alberto: Multivariate Statistical Methods: A Primer, 4th ed, 
Routledge/CRC Press, ISBN 1498728960; the 3rd edition will do as well.

These texts covers the main course material, with supplementary
notes for some subjects and supplementary exercises.

Course content overview:
Regression analysis (multiple linear regression and logistic regression
models)
Experimental design and multifactorial analysis
Methods for dealing with clustering
Multivariate analysis

Detailed course topics (keywords):
Simple linear and polynomial regression
Multiple linear regression and linear models
Logistic regression and generalized linear models
Model building, selection and assessment of confounding as well as regression 
  diagnostics for linear/logistic models
Multifactorial analysis of variance
Experimental designs: blocking versus replication,
complete/incomplete designs, Latin squares, cross-over designs
Methods for dealing with clustering in continuous and discrete data
Topics of multivariate analysis: multivariate inference, principal components 
  and factor analysis, multivariate distance and cluster analysis, classification, 
  canonical correlations and ordination
Primary statistical computer packages: Minitab and/or Stata
Additional statistical computer packages: SAS and R

Examination:
home assignments, course project and final take-home exam

Prerequisites:
equivalent to VHM 801 (see http://people.upei.ca/hstryhn/vhm801)
familiarity with a major statistical software package

Further information:
http://people.upei.ca/hstryhn/vhm802
(with a detailed schedule and links to homepages of previous years)