VHM 802, Advanced Veterinary Biostatistics (e-mail 12/12-2024)

Announcement of Biostats VHM 8020 course at AVC (UPEI)

Please find below an outline of the course VHM 802: Advanced Veterinary Biostatistics 
for the Winter Semester 2025. To (informally) connect with the course, send 
an e-mail with name and affiliation to hstryhn@upei.ca. You may also indicate 
if the schedule outlined below is inconvenient - the schedule may be changed to 
suit the participants better (conditional upon available rooms for lectures and labs).

Based on the current recommendations from UPEI, the plan is for a course with 
all sessions conducted in-person. Plans may be revised at any time as necessary 
based on recommendations from UPEI and the Public Health Office of PEI.

The course will be run in part jointly with VHM 8120: Epidemiology II. 
Students may take VHM 802 separately (3 credits) or in combination with VHM 812 
(taken simultaneously or in a previous year, 2 credits). Because of the choice 
between these two versions of the course, it is recommended that you connect 
with the course instructor before registering officially at the myUPEI web portal, 
in order to increase the chance of getting registered correctly!

The course content may be adapted from the general outline below to match 
specific student interests; in particular, it is possible to include sessions 
on multivariate analysis, which constituted a major part of the course in the 
winter semesters of 2023 and 2024. The course may not be offered if the number 
of students registered is too low.

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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Biostats VHM 802 Course - Winter Semester 2025

Preliminary schedule:
- time: January 8 - April 10; first session January 8, 1-4pm.
- lectures joint with VHM 812:
  Wednesdays 1-4pm and Fridays 9am-12pm in AVC 278N, 8/1-7/2 and one week in March,
- lectures for VHM 802 only:
  Thursdays 9-11am in AVC 278N, 13/2-10/4 (excl one week in March),
- labs: Mondays 1-4pm (mostly) in AVC 218S (computer lab), start 14/2

Course format:
Weekly lectures reviewing the theory and working through minor
exercises, supplemented by weekly lab sessions containing tutorials
of statistical software, individual work (statistical analyses) using
computers, discussions and student presentations. In weeks taught
jointly with VHM 812, the course has two lecture/review sessions instead
of one lecture and one lab session.
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 and 16 of Dohoo, Martin and Stryhn: Veterinary
Epidemiological Research; students not taking the epi 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/.

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 ANOVA analysis (multifactorial models)
Random effects models and repeated measures models
Power and sample size
Option for material on multivariate analysis

Detailed course topics (keywords):
Simple linear and polynomial regression
Multiple linear regression (model selection, regression diagnostics)
Analysis of covariance and General linear models
Logistic regression and generalized linear models
Analysis of variance (1-way, 2-way and multifactorial),
Experimental designs: blocking versus replication,
complete/incomplete designs, Latin squares and balanced
incomplete designs, cross-over designs, fractional designs,
Random effects models (e.g. split-plot designs and hierarchically
nested factors)
Repeated measures models and analysis
Methods for dealing with clustering in continuous and discrete data
Power and sample size calculation in simple and complex models
Option for multivariate topics: principal components and factor analysis, 
cluster analysis, classification methods
Primary statistical computer packages: Minitab and/or Stata
Additional statistical computer packages: SAS and R

Examination:
home assignments, course project and final exam

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

Further information:
http://stryhnstatistics.ca/vhm802
(with a more detailed schedule and links to previous years' homepages)