Courses & Timetables

willy [dot] wynant [at] mail [dot] mcgill [dot] ca (W. Wynant)

Basic principles of statistical inference applicable to clinical, epidemiologic, and other health research. Topics include: methods of describing data, statistical inference for means, statistical inference for proportions, non-parametric statistics, correlation and introduction to linear regression.

Prerequisite(s): Permission of instructor

Restriction(s): Restricted to students registered in Occupational Health, Dentistry, Rehabilitation Sciences, Human Nutrition, Experimental Medicine-Family Medicine Option, Otolaringology, Medical Residents, and Clinical Fellows.

NOTES: Medical Residents & Clinical Fellows can register for this course only during the Summer term.

Course not opened to students registered in the Epidemiology and Biostatistics programs.

Academic Credits: 3

amelie [dot] quesnelvallee [at] mcgill [dot] ca (Dr. A. Quesnel-Vallée)

Comparative perspective to illustrate processes involved in the development and evolution of health care systems around the world. Countries examined will represent different welfare state regimes, health care system typologies, levels of development and wealth.

Note: This course is cross-listed in Sociology.
Restriction: Not open to students who are taking or have taken SOCI 525.

Prerequisite: Permission of instructor.

Academic Credits: 3

erin [dot] strumpfloucks [at] mcgill [dot] ca (Dr. E. Strumpf)

Key health policy topics in developed economies using analytic frameworks and tools from economics. Major topics include health insurance, health care financing, and the roles of individuals and public and private institutions in the health care system.

NOTE: This course is open to graduate students and advanced undergraduates from all departments, with the permission of the instructor. A background in introductory economics is useful, though not required.

Academic Credits: 3

eric [dot] latimer [at] douglas [dot] mcgill [dot] ca (Dr. E. Latimer)

Concepts and methods used to carry out economic evaluations of health programmes and interventions, including public health interventions, pharmaceuticals, and other health care interventions. Includes topics such as calculation of unit costs, measurement of quality-adjusted life years (QALYs) and assessment of uncertainty in cost-effectiveness analysis.

Note: This course is open to graduate students and advanced undergraduates from all departments, with the permission of the instructor. No prior background in economics is required.

Academic Credits: 3

antonio [dot] ciampi [at] mcgill [dot] ca (Dr. Antonio Ciampi)

The aim of this course is to provide students with basic principles of regression analyses applicable to the health sciences so that they can understand and use appropriate statistical regression techniques for continuous and discrete data.

Prerequisite: EPIB 507.

Restricted to students registered in Occupational Health, Dentistry, Rehabilitation Sciences, Human Nutrition, Experimental Medicine-Family Medicine Option, Otolaringology, Medical Residents, and Clinical Fellows.

Course not open to students in Epidemiology, Biostatistics and MScPH programs.

Academic Credits: 3

Section 001 - arijit [dot] nandi [at] mcgill [dot] ca (Dr. A. Nandi)

Section 002 - lisa [dot] kakinami [at] mcgill [dot] ca (Dr. L. Kakinami)

This course aims to provide a comprehensive introduction to modern epidemiologic concepts and methods. It is designed for graduate students in the MSc and PhD degree programs of the Department of Epidemiology and Biostatistics. This course provides, at the graduate level, fundamental concepts, principles, and methods of epidemiologic research and study design. Topics include definitions, measures of disease frequency and effect, epidemiologic study designs, biases and confounding. In addition to lectures, students will participate in a practicum/laboratory session where they will engage in case studies, group discussions, journal article appraisals, and work on problem sets, quizzes, and lab exercises. The companion courses, 602 and 603, will cover other introductory topics in epidemiology and biostatistics.

Prerequisites: Concurrent enrollment in EPIB 602 for students in Epidemiology and Public Health programs.
Restriction: Not open to students who have taken EPIB 606.
Section 001 restricted to students in the Epidemiology, Biostatistics and Public Health programs.
Section 002 not opened to students in the Epidemiology, Biostatistics and Public Health programs.

Academic Credits: 4

gilles [dot] paradis [at] mcgill [dot] ca (Dr. G. Paradis)

EPIB 602 is a companion course to EPIB 601. The course is intended for graduate students in the epidemiology degree programs and is required for MSc students in Epidemiology as well as MSc students in Public Health. The course focuses on three main topics: descriptive epidemiology, sampling methods and measurement. Specific topics will include an introduction to population-based studies, life table and basic survival analysis, probability and non-probability-based sampling, sampling error, sample size estimation, principles of exposure measurement, measurement error, validity, reliability, questionnaire design and other concepts and methods.

Prerequisites: Concurrent enrollment in EPIB 601 and 607.
Restricted to students in the Department of Epidemiology, Biostatistics and Occupational Health.

Academic Credits: 3

jay [dot] kaufman [at] mcgill [dot] ca (Dr. J. Kaufman)

Estimation of epidemiologic effect measures and their confidence intervals in a variety of different study designs. Emphasis on analysis of sample data sets using regression models, graphical and tabular presentation of results, causal interpretation of effect estimates, writing reports for scientific publications, and sensitivity analyses for violated assumptions.

Prerequisites: EPIB 603 and EPIB 621 or equivalent
Restriction: Open to Ph.D. students in Epidemiology or Biostatistics programs only

Academic Credits: 3

olli [dot] saarela [at] mcgill [dot] ca (Dr. O. Saarela)

The aim of this course is to provide students with basic principles of statistical inference applicable to clinical and epidemiologic research so that they can: i) understand how statistical methods are used by others; (ii) apply statistical methods in their own research; (iii) use the methods learned in this course as a foundation for more advanced biostatistics courses. Topics include sampling, methods of describing data, introduction to probability, introduction to statistical inference, correlation and an introduction to regression.

Prerequisites: At least one course which includes differential and integral calculus.
Restricted to students in the Department of Epidemiology, Biostatistics and Occupational Health.

Academic Credits: 4

The two primary learning objectives of this course are to contribute to the training of PhD students in their quest to become independent scientists and to provide opportunities for supervised classroom teaching of epidemiological and biostatistical methods. These objectives will be achieved through directed readings, presentations and discussions. Topics also include the development of epidemiological methods and selected current epidemiological controversies.

Prerequisite(s): successful completion of the PhD preparatory year curriculum (or equivalent courses taken elsewhere) or permission of instructor.

Restriction(s): Restricted to Ph.D. students in the Department of Epidemiology, Biostatistics and Occupational Health

Academic Credit: 3

Introduction to statistical software and fundamentals of data management – data entering, manipulating data and elementary statistical analysis in Epidemiology using software such as STATA and R.

Prerequisite: Enrolment in Epidemiology program.

Academic Credit: 1

christina [dot] wolfson [at] mcgill [dot] ca (Dr. C. Wolfson)

Lectures and discussions plus oral and written presentations by students, to provide guidance and experience in the development of objectives, for the formulation and constructive peer criticism of designs for research in the health sciences, including etiologic and evaluative, cross-sectional, case-reference and cohort studies.

Prerequisite: EPIB 601 and EPIB 602.

Restrictions: Registration restricted to students in the Ph.D. Epidemiology program.

Academic Credits: 3

nicholas [dot] king [at] mcgill [dot] ca (Dr. N. King)

This graduate course addresses the ethical evaluation of population approaches to health and public health theory and practice. Students will discuss ethical dilemmas that arise in specific case studies in public health. Topics include (but will not be limited to): determinants of health, health inequalities, and social justice; genetics and racial categorization in public health; DALYs and the appropriate definition of health; biodefense and the 'militarization' of public health; surveillance and privacy; pandemic preparedness and distribution of scarce resources during an epidemic; environmental health and cost-benefit analysis; and isolation, quarantine and compliance. Students from any disciplinary background are welcome; there are no prerequisites. Coursework includes reading scholarly literature; formal presentation and debate; case analysis; and written work. Course materials draw on a wide range of disciplines, including epidemiology, medicine, history, sociology, and anthropology.

Not opened to students who took EPIB 678

Academic Credits: 3

norbert [dot] schmitz [at] douglas [dot] mcgill [dot] ca (Dr. N. Schmitz)

This course will focus on methodological issues related to measures of health status, determinants of health status, and other relevant covariates encountered in clinical and epidemiologic research. Topics to be covered include instrument development, assessment of reliability and validity, item response theory, and latent variable-based measurement models.

Prerequisites: EPIB 603 and EPIB 621 or permission of instructor.

Academic Credits: 3

rebecca [dot] fuhrer [at] mcgill [dot] ca (Dr. R. Fuhrer)

Students will critically assess research and summarize the findings in a research paper on a health related topic from a public health perspective. Topic to be approved by faculty member who will direct student and evaluate the paper.

Restriction: Restricted to Master's of Public Health students who have completed requirements.

Academic Credits: 14

olga [dot] basso [at] mcgill [dot] ca (Dr. O. Basso)

The course will provide a brief overview of the concepts and principles underlying epidemiologic study designs. While most students will be familiar with the basics of study design, this course will focus on the importance of appropriately formulating the research question, identifying the target population, defining the relevant entities, and on how these factors can threaten the validity of study findings. Examples from the published literature will be extensively used to illustrate the crucial points and will be discussed in class.

Students taking the course are expected to know the basic epidemiologic concepts, including measures of disease status and occurrence, measures of association, bias and confounding. At the end of the course, students should have improved the critical skills required when reading an epidemiologic paper or planning a study.

Prerequisites: Open to Ph.D. in Epidemiology students, or permission of the instructor.

This course will start November 4, 2013.

Academic Credit: 1

sam [dot] harper [at] mcgill [dot] ca (Dr. S. Harper) jay [dot] kaufman [at] mcgill [dot] ca (Dr. J. Kaufman)

Methods for conducting studies in social epidemiology and population health will be covered. Topics will include causal inference; measurement and concepts of social exposures; methods for study design and analysis. Techniques for descriptive and etiologic investigations of socioeconomic position, gender, race and ethnicity, geography, and social policies will be discussed.

Prerequisites: EPIB 603 and EPIB 621, or permission of the instructors.

Academic Credit: 3

michal [dot] abrahamowicz [at] mcgill [dot] ca (Dr. M. Abrahamowicz)

This course in applied biostatistics aims at developing more advanced skills and insights into multivariable modeling. The main focus will be on flexible modeling of survival, i.e. time-to-event processes, in both etiologic epidemiological studies and in prognostic studies of disease progression and its treatment. We will learn how to model and interpret (i) time-dependent covariates, and (ii) associations which vary over time, i.e. time-varying effects, (iii) complex multi-dimensional time-dependent exposures, such as lifetime history of occupational exposure, , including (iv) cumulative effects. Extensions of survival analyses to (a) relative survival methods that deal with unknown causes of death, and (b) Markov multi-state modeling will be also discussed. We will also explore some methodological issues, ‘generic’ for any complex multivariable analyses, regardless of whether the outcome is continuous, binary or event time, such as flexible modeling of non-linear effects of continuous variables, as well as estimation and testing of interactions. We will introduce, at a non-technical, conceptual level, the role of computer simulations as an essential tool (e.g. to validate or assess novel methods) of modern methodological research in biostatistics and epidemiology.

Lectures will involve both (i) explanation of the underlying concepts and methodological principles, with main focus on why and when the method should be applied, and (ii) real-life epidemiological applications of these methods, with focus on both how the method was implemented and how the results should be interpreted.

The course is oriented toward 3 groups of graduate students: (i) PhD students in Epidemiology and Occupational Health streams may use some of these advanced methods in their doctoral (or future) research, (ii) methodologically-oriented MSc students in Epidemiology who enjoyed the mandatory courses in biostatistics, and are eager to learn more advanced methods, and (iii) PhD and MSc students in Biostatistics or Statistics (from Math & Stati Dept.), especially those who are interested in more applied aspects of biostatistical research.

Epidemiology students will learn to correctly interpret and critically evaluate the methods and results of such methods in modern epidemiological research, and to implement some, more user-friendly methods in their own data analyses. The Biostatistics/Statistics students, in addition, will gain some insight into the underlying theory of non-parametric modeling, and some ‘technical’ aspects of modeling and simulations.

Academic Credits: Epidemiology 3 | Biostatitistics 4

Pre-requisites:

For Epidemiology students: At Least 2 first courses in Statistics offered by the Department (EPIB 607 and EPIB 621), or equivalent, or the Instructor’s permission.

For Biostatistics students, and graduate students in Math&Stat Departments, there are no specific prerequisites but good understanding of multivariable regression and basic knowledge of survival analysis will be expected.

madhukar [dot] pai [at] mcgill [dot] ca (Dr. M. Pai)

Knowledge synthesis is critical for evidence-based clinical and public health practice. Systematic reviews are now considered an essential component of guideline and policy development. The widespread and growing application of systematic reviews to synthesize evidence on key research and clinical questions makes it useful for health professionals and graduate students to be able to understand and critique this research design, and to actually conduct such reviews. This course will provide a detailed description of the systematic review process, discuss the strengths and limitations of the method, and provide step-by-step guidance on how to actually perform a systematic review and meta-analysis. In fact, all enrolled students will be required to complete a systematic review (on a topic of their choice) during the course of the semester. The goal would be to produce a draft manuscript that can be submitted to peer-reviewed journals.

Specific topics to be covered include: formulation of the review question, searching of literature, quality assessment of studies, data extraction, meta-analytic methods, and report writing. The course will also cover statistical issues such as selection of statistical models for meta-analysis, practical examples of fixed and random effects models as well as examples of methods to evaluate heterogeneity and publication bias; graphical and tabular templates for the presentation of meta-analysis data. STATA software package will be extensively used, along with computer lab tutorials on how to effectively use tools such as PubMed, Embase and EndNote for conducting reviews. This course will feature invited speakers who will provide overviews of special topics such as network meta-analyses, diagnostic meta-analyses, individual patient-data meta-analyses, and Bayesian meta-analyses.

This course builds on EPIB619, a popular 2-credit summer course on systematic reviews and meta-analyses. Previous course materials are available at: www.teachepi.org

Academic credits: 3

Prerequisites: Introductory level training in epidemiology (e.g. EPIB601) and biostatistics (e.g. EPIB607).

This course is restricted to students in the Department of Epidemiology, Biostatistics and Occupational Health.

lawrence [dot] joseph [at] mcgill [dot] ca (Dr. L. Joseph)

Introduction to practical Bayesian methods. Topics will include Bayesian philosophy, simple Bayesian models including linear and logistic regression, hierarchical models, and numerical techniques, including an introduction to the Gibbs sampler. Programming in R and WinBUGS.

Prerequisite: EPIB 607 and EPIB 621 or permission of the instructor.

Restriction: Not opened to students who took EPIB 668

Academic Credits: 2

claire [dot] infante-rivard [at] mcgill [dot] ca (Dr. C. Infante-Rivard)

The comprehensive examination is a written examination. The objective is to assess the degree to which doctoral students have been able to assimilate and apply the principles of epidemiologic research. Examination held yearly.

[Course Secure Webpage]

Academic Credits: 0

micheal [dot] kramer [at] mcgill [dot] ca (Dr. M. Kramer) / michal [dot] abrahamowicz [at] mcgill [dot] ca (Dr. M. Abrahamowicz)

The course will prepare students for their research PhD proposal. Students will acquire essential skills for writing and defense, including essential elements of research protocols, including the formulation of research objectives, the design, and strategies. The elements will be adapted to the epidemiology or biostatistics context.

Students will normally take this course in the year following the completion of their PhD Comprehensive Examinations. Students are expected, under the active tutelage of their supervisors and thesis committee members, to have developed a scientifically appropriate research question that will be addressed by rigorous research methods of the highest quality. Students need to demonstrate essential grantmanship skills in both writing and defending their protocol, including essential elements of research protocols, such as the formulation of research objectives, the design, and epidemiological and biostatistical methods appropriate for the specific context of their research.

The course is run over the Fall and Winter terms. It will not be offered during the summer months. The course will meet every week that a presentation is scheduled. It is expected that all students enrolled in a given academic year will attend all presentations by their fellow students in both semesters, regardless of the timing of their own protocol defenses (unless their absence at a specific class is approved by the course instructors). In the first week of the Fall semester, the students will meet with the course instructors to discuss the goals, expectations, procedures and – as far as possible – to prevent future misunderstandings.

Course Outline [.pdf]

jean-f [dot] boivin@mcgill [dot] ca [at] mcgill [dot] ca (Dr. J.-F. Boivin)

This course presents concepts and methods of epidemiology at the introductory level. The use of epidemiologic methods for population and public health research and practice will be illustrated. A review of selected population health questions such as the HIV/AIDS epidemic, the cardiovascular disease epidemic, cigarette smoking, or screening for disease will be presented.

Course not open to students enrolled in Epidemiology or Public Health Programs.

Academic Credits: 3

eric [dot] latimer [at] mcgill [dot] ca (Dr. E. Latimer)

After a brief description of the organization of the Canadian health care system, and an overview of basic economic theory (utility, profit maximization, demand and supply, competitive markets and the “invisible hand”) this course will introduce a number of key concepts from health economics that are helpful for formulating health care policy: asymmetric information between physicians and patients and supplier-induced demand, incentive effects of various forms of physician payment and hospital funding, different ways of allowing parallel private insurance and their effects on accessibility, quality and costs. The second half of the course will focus on economic evaluation of health interventions: in particular, cost-effectiveness and cost-utility analysis (perspective of an economic analysis, discounting, measuring health-related quality of life, Quality-adjusted life years, etc.). No prerequisites, but permission from the instructor is required for students from outside the Department of Epidemiology and Biostatistics, and Occupational Health, or the Department of Economics.

Academic Credits: 3

sam [dot] harper [at] mcgill [dot] ca (Dr. S. Harper)

This course presents concepts and methods for epidemiology at the intermediate level. It is designed for students interested in conducting epidemiologic research autonomously. The course covers: concepts of causation, measures of disease occurrence and effect, study designs, biases in epidemiologic research, and interaction. Critical assessment of the literature is emphasized.

Prerequisites: EPIB 601, EPIB 602 and EPIB 607.
Restricted to students in the Department of Epidemiology, Biostatistics and Occupational Health.

Academic Credits: 4

maida [dot] sewitch [at] mcgill [dot] ca (Dr. M. Sewitch)

This course provides the opportunity to develop skills to critically evaluate evidence presented in the biomedical and health sciences literature, based on the concepts acquired in the epidemiology introductory courses.

Prerequisites: EPIB 601 and EPIB 607.
Restricted to students in the Department of Epidemiology, Biostatistics and Occupational Health.

Academic Credit: 1

claire [dot] infante-rivard [at] mcgill [dot] ca (Dr. C. Infante-Rivard) /Dr. J. Chevrier Fremont

The objective of this course is to reinforce what students already know about epidemiologic methods, and to broaden and deepen their understanding of issues related to "time" in epidemiology. The course will focus on the design and analysis of studies where time-varying patterns of occurrence of outcome events and exposure measures are of particular relevance. Classical and newer study designs and statistical analyses, as well as their associated biases are discussed. The course will involve both lectures and seminars. The seminar component will be based on student presentations of papers followed by general discussion.

Prerequisite: Students should have completed the introductory courses in epidemiology and biostatistics (EPIB 601, EPIB 602, EPIB 607 and EPIB 621 or the equivalent courses) or have permission from the instructors.

Restriction: Open to Ph.D. students in Epidemiology or Biostatistics programs only

Academic Credits: 3

tibor [dot] schuster [at] mcgill [dot] ca (Dr. T. Shuster)

Conceptual and methodological issues in epidemiology and biostatistics related to causal inference.

Prerequisite(s): EPIB 608, or equivalent, or permission of instructor

Restriction(s): Restricted to Ph.D. students in the Department of Epidemiology, Biostatistics and Occupational Health

Academic Credit: 3

david [dot] buckeridge [at] mcgill [dot] ca (Dr. D. Buckeridge)

Epidemiology & Biostatistics: Principles and methods in public health practice. Topics will include investigation in public health, public health intervention, program evaluation, public health and the health care system, society and public health.

Prequisites: EPIB 601, EPIB 602, and EPIB 607 or permission of instructor

Restriction: Open only to students in the MSc and PhD programs in Epidemiology, Biostatistics and Occupational Health. Open to students in other disciplines with permission of instructor.

Academic Credit: 3

jane [dot] mccusker [at] mcgill [dot] ca (Dr. J.McCusker)

The course will review principles that can be applied to measuring a wide range of exposures, as well as outcomes. Accurate measurement is essential to the validity of epidemiological research.Topics to be covered include measurement error, and the design, analysis, and interpretation of validity and reliability studies.

Prerequisites: EPIB 601, EPIB 602 and EPIB 607

Restriction: Open only to students in the M.Sc. and Ph.D. programs in Epidemiology, Biostatistics and Occupational Health.

Academic Credits: 1

caroline [dot] quach [at] mcgill [dot] ca (Dr. C. Quach)

Introduction to the field of infectious disease epidemiology taught from a public health perspective. Topics include analytic methods, study design, outbreak investigations, surveillance, vaccine development and evaluations, screening, modeling, and infectious causes of cancer or chronic diseases.

Prerequisite: EPIB 601 or Permission of Instructor.

Note: An undergraduate level biology course is highly recommended.

Syllabus [PDF]

Academic Credits: 3

aurelie [dot] labbe [at] mcgill [dot] ca (Dr. A. Labbe)

Univariate and multivariate statistical techniques for continuous categorical data. Topics include generalized linear models, multiple linear and logistic regression and model selection. Maximum likelihood and Bayesian approaches will be presented.

Prerequisites: EPIB 601, and EPIB 607 or permission of instructor.
Restricted to students in the Department of Epidemiology, Biostatistics and Occupational Health.

Academic Credits: 4

jonathan [dot] kimmelman [at] mcgill [dot] ca (Dr. J. Kimmelman)

Some of the earliest and foundational debates in bioethics grew out of revelations about abuses in human experimentation. This class provides an introduction to the ethics of conducting research involving human beings. Though there is a particular focus on clinical trials, the course also surveys ethical issues in public health research, experimental psychology, and animal experimentation. Areas to be covered include the following: (1) scandals involving research with humans; (2) ethical and regulatory guidelines and structures; (3) ethical theory and principles of human research ethics; (4) empirical literature on ethical practice. The course is additionally intended to help students develop skills needed to perform academic research in biomedical ethics.

Not opened to students who took EPIB 679

Academic Credit: 3

Dr. P. Chaudhuri

The course will provide a basic introduction to methods for analysis of correlated, or dependent, data. These data arise when observations are not gathered independently; examples are longitudinal data, household data, cluster samples, etc. basic descriptive methods and introduce regression methods for both continuous and discrete outcomes will be examined

Prerequisites: EPIB 603, EPIB 621.

Academic Credits: 3

rebecca [dot] fuhrer [at] mcgill [dot] ca (Dr. R. Fuhrer)

Students will critically assess research and summarize the findings in a research paper on a health related topic from a public health perspective. Topic to be approved by faculty member who will direct student and evaluate the paper.

Restriction: Restricted to Master's of Public Health students who have completed requirements.

Academic Credits: 14

Dr. Jill Baumgartner

This course will introduce students to grand challenges in global health related to environmental and occupational risks, and the multi-disciplinary methods used to identify, control, and prevent them. We will focus on environmental issues, such as air pollution, pesticides, toxic metals, unsafe water and sanitation, analyze their impacts on the global burden of disease, including asthma, malaria, cardiovascular disease, and child development; review the state of the science emerging threats such as the impacts of climate change and urbanization on shifting disease patterns; and identify key interventions and policies to address these pressing global health topics in both industrialized and developing countries. Students will develop knowledge and skills in core disciplines of environmental health (toxicology, exposure science, environmental epidemiology) and approaches to environmental risk recognition, control and prevention in a global context.

Academic Credits: 3

theresa [dot] gyorkos [at] mcgill [dot] ca (Dr. T. Gyorkos)

A review of selected epidemiological research focussing on global health and disease issues. Research will be mostly from developing countries and research methods will be highlighted.

Prerequisite: Permission of the instructor.

Please note this course has a minimum requirement of 5 registrations. It will be cancelled if minimum is not met.

Academic Credits: 3

lawrence [dot] joseph [at] mcgill [dot] ca " rel="nofollow">Dr. L. Joseph

Bayesian design and analysis with applications specifically geared towards epidemiological research. Topics may include multi-leveled hierarchical models, diagnostic tests, Bayesian sample size methods, issues in clinical trials, measurement error and missing data problems. Programming in R and WinBUGS.

Prerequisite: EPIB 682 (Introduction to Bayesian Analysis in Health Sciences) or permission of the instructor.

Restriction: Not opened to students who took EPIB 669

Academic Credits: 2

claire [dot] infante-rivard [at] mcgill [dot] ca (Dr. C. Infante-Rivard)

The comprehensive examination is a written examination. The objective is to assess the degree to which doctoral students have been able to assimilate and apply the principles of epidemiologic research. Examination held yearly.

[Course Secure Webpage]

Academic Credits: 0

micheal [dot] kramer [at] mcgill [dot] ca (Dr. M. Kramer) / michal [dot] abrahamowicz [at] mcgill [dot] ca (Dr. M. Abrahamowicz)

The course will prepare students for their research PhD proposal. Students will acquire essential skills for writing and defense, including essential elements of research protocols, including the formulation of research objectives, the design, and strategies. The elements will be adapted to the epidemiology or biostatistics context.

Students will normally take this course in the year following the completion of their PhD Comprehensive Examinations. Students are expected, under the active tutelage of their supervisors and thesis committee members, to have developed a scientifically appropriate research question that will be addressed by rigorous research methods of the highest quality. Students need to demonstrate essential grantmanship skills in both writing and defending their protocol, including essential elements of research protocols, such as the formulation of research objectives, the design, and epidemiological and biostatistical methods appropriate for the specific context of their research.

The course is run over the Fall and Winter terms. It will not be offered during the summer months. The course will meet every week that a presentation is scheduled. It is expected that all students enrolled in a given academic year will attend all presentations by their fellow students in both semesters, regardless of the timing of their own protocol defenses (unless their absence at a specific class is approved by the course instructors). In the first week of the Fall semester, the students will meet with the course instructors to discuss the goals, expectations, procedures and – as far as possible – to prevent future misunderstandings.

Course Outline [.pdf]