The primary objective of the PhD program is to train epidemiologists as independent investigators in an academic or equivalent research positions, or in a position of professional leadership in a health or health related agency where research is an important function.
In order to successfully complete the PhD in Epidemiology, students are required to complete EPID 823, EPID 901, a comprehensive examination and a thesis. In addition to required courses, students are encouraged to take additional elective courses, as deemed appropriate by their Supervisor(s). The following provides a brief overview of the difference course requirements of the PhD in Epidemiology program:
An advanced course in the theoretical issues and analytical practices in epidemiology, and biostatistics. Major topics include the life-table method, demography and confounding and its solutions. Detailed design and analysis of cohort, case-referent and experimental studies shall be performed. Multifactor techniques including log-linear logistic and Cox's proportional hazards models will be discussed in detail. Three term-hours. Fall every year. M. McIsaac, D. Tu, P. Groome, W King.
PREREQUISITE: EPID 822 or equivalent+ (+ "equivalent" option applicable to M.Sc. Collaborative Biostatistics students only)
This course provides in-depth integration of advanced concepts in epidemiology, with theory and examples, including causation and causal inference, study design and conduct, alternate designs, confounding, effect modification, internal and external validity, misclassification, source populations, statistical power and sample size, epidemiologic data analysis and interpretation, meta-analysis and selected specific research areas. This is an advanced course intended primarily for Ph.D. students. Sessions consist of lectures, seminars, student presentations and discussions.
Three term- hours, fall and winter. W. King, W. Pickett, fall term; P. Groome, L. Levesque, winter term.
PREREQUISITES: EPID 801, EPID 804, EPID 821 and EPID 822 or equivalent from other institutions.
All Doctoral students must pass a Comprehensive Exam. Students will be evaluated for their in-depth knowledge in theoretical and applied epidemiologic and biostatistical methods; and, theoretical and applied knowledge in their stream and specific topic area.
To assist in preparing for the examination, students will be provided with a recommended reading list of key texts. They will be expected to prepare for the comprehensive examination mainly through self-directed study, although informal sessions to aid preparation will be arranged and faculty consultation will be encouraged.
The exam will usually take place after all coursework has been completed in June of the first year of study. It will contain a written and an oral component. Specific content and format will be determined by a Comprehensive Examination Committee.
Students must prepare and successfully defend a PhD Thesis Research Project (EPID 999). Through the dissertation process, students will demonstrate their ability to undertake epidemiologic studies, including the ability to:
- critically appraise and synthesize biomedical literature surrounding epidemiologic topics and concepts;
- develop novel hypotheses that can be examined via epidemiological study;
- develop practical epidemiological study designs aimed at testing these hypotheses and write scientific protocols that summarize research plans;
- collect, analyze, and interpret data; and,
- understand the implications of findings within appropriate population health, health services/policy, or clinical contexts.
Recent Doctoral Theses can be accessed on the PhD student profile page: https://webpublish.queensu.ca/phswww/phd-epidemiology/student-profiles-p...
The PhD in Epidemiology is a 4 year degree with the following milestones;
||Completion of Core Courses (fall and winter terms)
Completion of Comprehensive Examination (summer terms)
||Completion of Thesis Outline (15 months)
Completion of Thesis Proposal (24 months)
|Research and data collection
Completion of research and data collection
Writing of thesis