Updated note on COVID-19 consequences for the 2020 Summer Course program:
– Module 1 will take place August 17 – 28 (details below);
– Module 2 and Module 3 are cancelled or postponed (time unknown);
– Registration for Module 1 is now open.
Introduction to Multilevel Modelling
Aug 17 – 28 (schedule)
Instructors: Professors Ian Dohoo and Henrik Stryhn
CVER, AVC, University of Prince Edward Island (UPEI)
The 10-day course is designed to provide participants with the knowledge and skills required to successfully fit multilevel models to both continuous data (linear models) and discrete data (emphasis on logistic and Poisson models). The presentation of theoretical background material is limited to that which is required for a reasonable understanding of the methods employed. Specific topics covered in the course include: introduction to multilevel/hierarchical data, mixed models for continuous data, mixed models for discrete data, model evaluation (diagnostics), analysis of repeated measures and alternative approaches to dealing with clustered data (including Bayesian methods). The main software used for the instruction is MLwiN, but the code for fitting models in additional software packages (including Stata and R) will also be provided.
The course allows both in-class and online participation, where the former is restricted to local participants meeting UPEI’s conditions for access to the campus. All sessions of the course will be streamed online by video-conferencing software, and all lectures and demonstrations will be recorded and made available to participants. Additionally, all course material will be accessible online. Only a limited number of online participants will be admitted to the course.
The following registration fees apply (amounts are in $Cdn and include taxes and administration fees):
Module 1: Introduction to Multilevel Modelling
Participant Course Fees Student* 550 Non-student 1000
*Proof of enrollment in a graduate program at a university (not necessarily UPEI) required
Click on the following Eventbrite logo to register for Module 1 of the Epi on the Island Summer Course 2020.
For further inquiries, including requests to be put on a waiting list, please contact Jenny Yu at firstname.lastname@example.org.
Asking Questions That People Can and Want to Answer
– Questionnaire Design and Measurement Scales
June 22 – 26 (schedule)
Instructor: Dr. Marika Wenemark, Adjunct Senior Lecturer, Division of Community Medicine, Department of Medical and Health Sciences,
Linköping University, Sweden
Instructor: Dr. Ian Dohoo, Professor Emeritus, CVER, AVC, UPEI
Perhaps you are one of the many people who have thought … “Developing a questionnaire can’t be very difficult”, or “Evaluating a producer’s attitude toward antibiotics should be pretty straightforward”. Maybe you want to think again. The literature is full of studies based on questionnaires that were poorly designed, badly executed, and had terrible response rates. Many of those investigators will have combined answers to multiple questions and pretended the results were a good measurement of something (even if they are not sure what).
This course will teach you how to develop a questionnaire which people can answer (and hence produce valid responses) and want to answer (hence providing a better response rate).
The questionnaire design topic will cover basic principles in writing questions and choosing the right response options, but we will also enter the respondent’s mind through knowledge of the cognitive process to answer questions and learn how that knowledge can be used to write effective questions that are easy to understand and answer. The course will also focus on different ways to test and evaluate survey questions as well as how to motivate people to take part in your survey.
Frequently we want to come up with estimates of quantities which cannot be measured directly, such as a producer’s attitude toward antibiotic resistance, or an overall measure of hygiene on a dairy farm. To come up with this summary measure, we need to combine data from multiple questions or observations into an overall scale. Methods to do this have been well developed in education and psychology, but have been little used in veterinary epidemiology. This course will teach you how to develop effective measurement scales. Specific topics to be covered include: introduction to scales; classical scale evaluation; introduction to item response theory (IRT) models; IRT models for binary data; IRT models for ordinal data; and constructing scales.
Econ on the Island – An Introduction to Health Economics
July 6 – 10 (schedule)
Instructor: Dr. Mike Paulden, Assistant Professor
School of Public Health, University of Alberta
Instructor: Dr. David C. Hall, Associate Professor, Animal Health Economics and Policy, Faculty of Veterinary Medicine, University of Calgary
This 5-day course provides an introduction to health economics applicable from the perspectives of both human and animal health professionals. A blend of examples, methodologies, and hands-on activities will be presented covering topics in both human health (e.g., program effectiveness, cost of illness to society) and animal health (e.g., impact of a zoonotic disease) that will be of interest and value to both groups of attendees. There will also be an opportunity to divide the class into two groups for more focused study with selected presentation to the entire class at the end of the week.
The course will emphasize understanding concepts and awareness of methodologies ranging from introductory (e.g., basic benefit-cost ratios, allocation of costs, valuation of loss of productivity) to intermediate (e.g., choice variable analysis, cost to society of disease outbreaks, designing mitigation strategies). Most examples will be presented in a format consistent with spreadsheet modeling; limited use of regression techniques or more advanced methods will be provided depending on interest.
The course will be directed to graduate students, health professionals, and researchers. Participants are encouraged to bring their own problems to work with during the course.
For further inquiries, please contact Jenny Yu at email@example.com.