Graduate
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Course Descriptions
Enrolment priority is given to graduate students in the Epidemiology & Biostatistics graduate program. If there is space in the course, graduate students from other programs may register for a course provided they have: the required pre-requisites, permission of the course instructor and permission of their home program.
For a list of required and elective courses in each of our graduate programs, please review our graduate course information page. Course times, locations, and outlines are available by request from EpiBio@uwo.ca.
Notes:
"A" courses are offered in the fall term.
"Q" courses are offered in the first half of fall term.
"R" courses are offered in the second half of fall term.
"Q" courses are offered in the first half of fall term.
"R" courses are offered in the second half of fall term.
"B" courses are offered in the winter term.
"S" courses are offered in the first half of winter term.
"T" courses are offered in the second half of winter term.
"U" and "V" courses are offered in the summer term.
"S" courses are offered in the first half of winter term.
"T" courses are offered in the second half of winter term.
"U" and "V" courses are offered in the summer term.
Biostatistics
Biostatistics 9509A: Principles of Biostatistics
Requirements: Must attend a one-hour orientation session held a week before start of class.
Course Weight: 0.5 credits
An introduction to applied biostatistics including: frequency distributions; sampling; testing means; testing proportions, and basic sample size estimations; one way analysis of variance, correlation and simple linear regression; non-parametric analyses. Introduction to the statistical computing program SAS.
Course Weight: 0.5 credits
An introduction to applied biostatistics including: frequency distributions; sampling; testing means; testing proportions, and basic sample size estimations; one way analysis of variance, correlation and simple linear regression; non-parametric analyses. Introduction to the statistical computing program SAS.
Biostatistics 9510A: Biostatistical Research Methods
Requirements: Required for Biostatistics students, and Epidemiology students if advised and permitted by their supervisor
Course Weight: 0.5 credits
Review of statistical methodology from epidemiological viewpoint, including cohort and case-control designs, relative odds (odds ratio) and relative risks. Introduction to computer simulation, and resampling methodology, including cross-validation and bootstrapping. Introduction to computer packages SAS, Splus/R and LaTeX.
Course Weight: 0.5 credits
Review of statistical methodology from epidemiological viewpoint, including cohort and case-control designs, relative odds (odds ratio) and relative risks. Introduction to computer simulation, and resampling methodology, including cross-validation and bootstrapping. Introduction to computer packages SAS, Splus/R and LaTeX.
Biostatistics 9521B: Multivariable Methods in Biostatistics
Prerequisite: Biostatistics 9509A or 9510A or equivalent
Antirequisite: Epidemiology 9512A
Course Weight: 0.5 credits
This course is designed to provide students with a conceptual understanding of multivariable regression models most often encountered by epidemiologists and biostatisticians. These include multiple linear regression models for continuous outcomes, logistic regression models for binary outcomes, and Cox proportional hazard regression models for time-to-event data. Models will be discussed in the contexts of isolating the effect of a single predictor, understanding multiple predictors, and outcome predictions. Statistical methods for longitudinal studies are also covered. By the end of the course students should be able to (i) understand and critique applications of regression models appearing in the biomedical literature and (ii) carry out their own analyses.
Antirequisite: Epidemiology 9512A
Course Weight: 0.5 credits
This course is designed to provide students with a conceptual understanding of multivariable regression models most often encountered by epidemiologists and biostatisticians. These include multiple linear regression models for continuous outcomes, logistic regression models for binary outcomes, and Cox proportional hazard regression models for time-to-event data. Models will be discussed in the contexts of isolating the effect of a single predictor, understanding multiple predictors, and outcome predictions. Statistical methods for longitudinal studies are also covered. By the end of the course students should be able to (i) understand and critique applications of regression models appearing in the biomedical literature and (ii) carry out their own analyses.
Biostatistics 9541U: Missing Data
Prerequisite: Epidemiology 9553B and Biostatistics 9521B
Course Weight: 0.25 credits
Study participants often do not provide all requested data, resulting in missing data. Most analytic procedures in statistical software quietly delete participants with missing values. Thus, missing data are a potential source of bias, and their handling in the statistical analysis can have an important impact on the likelihood and extent of bias. Inadequate handling of missing data may also result in invalid p-values and confidence intervals. This course introduces principled approaches to dealing with missing data arising from randomized controlled trials and observational studies. Students will have opportunity in analyzing studies with missing data using Stata and SAS.
Course Weight: 0.25 credits
Study participants often do not provide all requested data, resulting in missing data. Most analytic procedures in statistical software quietly delete participants with missing values. Thus, missing data are a potential source of bias, and their handling in the statistical analysis can have an important impact on the likelihood and extent of bias. Inadequate handling of missing data may also result in invalid p-values and confidence intervals. This course introduces principled approaches to dealing with missing data arising from randomized controlled trials and observational studies. Students will have opportunity in analyzing studies with missing data using Stata and SAS.
Biostatistics 9631R: Statistical Software
Prerequisite: Epidemiology 9553B and Biostatistics 9521B
Course Weight: 0.25 credits
This course introduces students to the use of both commercial software packages (i.e. SAS and Stata) and open-source software (R via RStudio) for data management, exploratory data analysis, and inferential statistical analysis. Examples analyzed using multiple software packages are used to illustrate the advantages and disadvantages of each package. Students should have an understanding of statistics at the level of multivariable methods.
Course Weight: 0.25 credits
This course introduces students to the use of both commercial software packages (i.e. SAS and Stata) and open-source software (R via RStudio) for data management, exploratory data analysis, and inferential statistical analysis. Examples analyzed using multiple software packages are used to illustrate the advantages and disadvantages of each package. Students should have an understanding of statistics at the level of multivariable methods.
Biostatistics 9651U: Multi-level Modelling
Prerequisite: Epidemiology 9553B and Biostatistics 9521B
Course Weight: 0.25 credits
This course covers statistical methods for drawing inferences from multi-level data, including longitudinal data from cohort studies and clinical trials, as well as multilevel data in social epidemiology. Topics include graphical exploration of data, and the use of linear and generalized linear regression models for correlated outcome data. Both marginal and random-effects models will be discussed. The course will have an applied emphasis using common statistical software packages (SAS, R and Stata).
Course Weight: 0.25 credits
This course covers statistical methods for drawing inferences from multi-level data, including longitudinal data from cohort studies and clinical trials, as well as multilevel data in social epidemiology. Topics include graphical exploration of data, and the use of linear and generalized linear regression models for correlated outcome data. Both marginal and random-effects models will be discussed. The course will have an applied emphasis using common statistical software packages (SAS, R and Stata).
Biostatistics 9681Q: Causal Modelling
Prerequisite: Epidemiology 9553B and Biostatistics 9521B
Course Weight: 0.25 credits
This course will take a rigorous approach to methods related to causal inference and counterfactual comparisons, including confounding, structuring causal models, analysing mediation, and heterogeneity of effect. Methods include propensity scores, causal diagrams, instrumental variables, regression discontinuity, marginal structural models, and average marginal risks.
Course Weight: 0.25 credits
This course will take a rigorous approach to methods related to causal inference and counterfactual comparisons, including confounding, structuring causal models, analysing mediation, and heterogeneity of effect. Methods include propensity scores, causal diagrams, instrumental variables, regression discontinuity, marginal structural models, and average marginal risks.
Epidemiology
Research Seminar I & II
Note: All first year students are required to attend the weekly departmental seminar series. This seminar series will appear on students’ transcripts as a complete or incomplete, based on students’ participation.
Course Weight: Milestone (non-credit, required)
The Epidemiology & Biostatistics Research Seminar course is designed to provide graduate students with a broader exposure to the applications of research methods and statistical approaches to research in Epidemiology and Biostatistics, help students develop critical appraisal skills, and provide students with exposure to a diverse group of health researchers to expand their familiarity with different research topics, perspectives, methods, data analytic strategies, and styles for presentation of research findings.
Course Weight: Milestone (non-credit, required)
The Epidemiology & Biostatistics Research Seminar course is designed to provide graduate students with a broader exposure to the applications of research methods and statistical approaches to research in Epidemiology and Biostatistics, help students develop critical appraisal skills, and provide students with exposure to a diverse group of health researchers to expand their familiarity with different research topics, perspectives, methods, data analytic strategies, and styles for presentation of research findings.
Epidemiology 9512Q: Questionnaire Design and Survey Implementation
Course Weight: 0.25 credits per course
This course provides an overview of effective questionnaire development and survey implementation techniques emphasizing the development of practical skills to optimize both the quantity and quality of survey data. The course stresses a tailored design strategy to reduce total survey error. Methods covered include: writing effective survey questions, questionnaire design principles, and effective communication with potential participants.
This course provides an overview of effective questionnaire development and survey implementation techniques emphasizing the development of practical skills to optimize both the quantity and quality of survey data. The course stresses a tailored design strategy to reduce total survey error. Methods covered include: writing effective survey questions, questionnaire design principles, and effective communication with potential participants.
Epidemiology 9514R: Sampling Methods
Course Weight: 0.25 credits per course
This course offers an introduction to the various techniques related to designing and executing population health surveys. Topics to be covered include: construction of sampling frames, basic sampling design concepts, estimation, and inference statistics. Upon successfully completing this course, students will have learned how to design and implement population surveys, estimate sample size for different sampling designs, estimate intraclass correlation coefficient and design-effects, compute sampling weights, and adjust for sampling non-response.
This course offers an introduction to the various techniques related to designing and executing population health surveys. Topics to be covered include: construction of sampling frames, basic sampling design concepts, estimation, and inference statistics. Upon successfully completing this course, students will have learned how to design and implement population surveys, estimate sample size for different sampling designs, estimate intraclass correlation coefficient and design-effects, compute sampling weights, and adjust for sampling non-response.
Epidemiology 9515B: Epidemiology of Major Diseases
Course Weight: 0.5 credits per course
A survey course covering the descriptive epidemiology (incidence and prevalence) and analytic epidemiology (risk and protective factors) of the infectious and chronic disease that are leading causes of death and disability. Effects of personal characteristics (age, gender), place (developing versus developed countries) and changes in occurrence over time are emphasized.
A survey course covering the descriptive epidemiology (incidence and prevalence) and analytic epidemiology (risk and protective factors) of the infectious and chronic disease that are leading causes of death and disability. Effects of personal characteristics (age, gender), place (developing versus developed countries) and changes in occurrence over time are emphasized.
Epidemiology 9516S: Analysis of Population Health Data
Course Weight: 0.25 credits per course
This course will familiarize students with selected statistical methods for the analysis of health-related survey data. In this hands-on seminar, students will learn how to address some of the methodological challenges of working with survey data. Students will develop their analytical skills by conducting a comprehensive analysis of a selected public health problem and by completing all stages of the research project, from conducting literature reviews to presenting the results.
This course will familiarize students with selected statistical methods for the analysis of health-related survey data. In this hands-on seminar, students will learn how to address some of the methodological challenges of working with survey data. Students will develop their analytical skills by conducting a comprehensive analysis of a selected public health problem and by completing all stages of the research project, from conducting literature reviews to presenting the results.
Epidemiology 9518T: Advanced Analysis of Population Health Data
Course Weight: 0.25 credits per course
This advanced course in Population Health analysis will explore in-depth topics on population health, beyond those covered in the introductory Population Health course (Epid 9516). Students will master their skills in statistical analysis of population health data, including presenting the results in the format of a public lectures and manuscripts.
This advanced course in Population Health analysis will explore in-depth topics on population health, beyond those covered in the introductory Population Health course (Epid 9516). Students will master their skills in statistical analysis of population health data, including presenting the results in the format of a public lectures and manuscripts.
Epidemiology 9526U: Grant Writing and Peer Review
Prerequisite: Epidemiology 9551A and Biostats 9509A or 9510A
Course Weight: 0.25 credits per course
This course will focus on professional skills development in proposal writing, and provide background on the Canadian funding environment. Strategies for presentation of proposed research, formative work with pilot data or background research, and grant structure will be covered. Students will also gain strategies and skills in peer reviewing grants and manuscripts.
Course Weight: 0.25 credits per course
This course will focus on professional skills development in proposal writing, and provide background on the Canadian funding environment. Strategies for presentation of proposed research, formative work with pilot data or background research, and grant structure will be covered. Students will also gain strategies and skills in peer reviewing grants and manuscripts.
Epidemiology 9530B: Health Economic Evaluation
Prerequisite: Epidemiology 9572Q
Course Weight: 0.50 credits per course
This course is designed to give students a solid background in health economics and its application in the field of health and medicine. The course objectives are to provide the student with an understanding of the theoretical economic foundation of health economics and methods for the economic evaluation of health interventions. The topics to be covered are: microeconomic tools for health economics, production of health, demand for healthcare and health insurance, market failure in the health sector, measures of costs, measures of health outcomes, discounting, cost-minimization analysis, cost-effectiveness analysis, cost-utility analysis, cost-benefit analysis, uncertainty in economic evaluation, decision-analytic models, Markov models, sensitivity analysis, and Monte Carlo simulation. This course will also provide the student with a hands-on experience in conducting economic evaluation using TreeAge Pro software package.
Course Weight: 0.50 credits per course
This course is designed to give students a solid background in health economics and its application in the field of health and medicine. The course objectives are to provide the student with an understanding of the theoretical economic foundation of health economics and methods for the economic evaluation of health interventions. The topics to be covered are: microeconomic tools for health economics, production of health, demand for healthcare and health insurance, market failure in the health sector, measures of costs, measures of health outcomes, discounting, cost-minimization analysis, cost-effectiveness analysis, cost-utility analysis, cost-benefit analysis, uncertainty in economic evaluation, decision-analytic models, Markov models, sensitivity analysis, and Monte Carlo simulation. This course will also provide the student with a hands-on experience in conducting economic evaluation using TreeAge Pro software package.
Epidemiology 9540R: Health Service Research Methods
Course Weight: 0.25 credits
This course aims to provide a broad overview of the basic concepts and methods for undertaking health services research. The emphasis is on the application of epidemiologic methods to topics related to the delivery, utilization, and outcomes of health services. The intent is to familiarize students interested in conducting health services research with key concepts, tools, and ideas that can support them in assessing the quality of existing studies and developing their own research proposals.
This course aims to provide a broad overview of the basic concepts and methods for undertaking health services research. The emphasis is on the application of epidemiologic methods to topics related to the delivery, utilization, and outcomes of health services. The intent is to familiarize students interested in conducting health services research with key concepts, tools, and ideas that can support them in assessing the quality of existing studies and developing their own research proposals.
Epidemiology 9551A: Foundations of Epidemiology
Course Weight: 0.5 credits
History, concepts and terminology of epidemiology. Basic types of epidemiological investigation, including strategies for infectious and chronic disease. Outline of important epidemiological variables.
History, concepts and terminology of epidemiology. Basic types of epidemiological investigation, including strategies for infectious and chronic disease. Outline of important epidemiological variables.
Epidemiology 9553B: Analytic Epidemiology
Prerequisites: Epidemiology 9551A and one of Biostatistics 9509A or Biostatistics 9510A or equivalents
Course Weight: 0.5 credits
This course introduces advanced theoretical concepts and methods in the study of causal questions using observational data. Topics include counterfactual theory; individual, group, and multi-level designs; mediation; heterogeneity of effects; confounding; and methods to address each of these. The development and critique of study protocols is a substantial course requirement.
Course Weight: 0.5 credits
This course introduces advanced theoretical concepts and methods in the study of causal questions using observational data. Topics include counterfactual theory; individual, group, and multi-level designs; mediation; heterogeneity of effects; confounding; and methods to address each of these. The development and critique of study protocols is a substantial course requirement.
Epidemiology 9562B: Clinical Epidemiology
Course Weight: 0.5 credits
A seminar course for health care professionals and epidemiology students that surveys the main topics in clinical epidemiology at an introductory level. The seminars focus on the design and evaluation of clinical studies that evaluate health-care related activities, and judging whether clinicians should, or should not, adapt the activity into their practice. The main topics include evaluation of studies that assess diagnostic tests, prognosis, therapy, early detection activities (screening and case-finding), etiology, and clinical prediction rules; introduction to meta-analysis; and variation and disagreement.
A seminar course for health care professionals and epidemiology students that surveys the main topics in clinical epidemiology at an introductory level. The seminars focus on the design and evaluation of clinical studies that evaluate health-care related activities, and judging whether clinicians should, or should not, adapt the activity into their practice. The main topics include evaluation of studies that assess diagnostic tests, prognosis, therapy, early detection activities (screening and case-finding), etiology, and clinical prediction rules; introduction to meta-analysis; and variation and disagreement.
Epidemiology 9566S: Randomized Trials: Design
Co-requisite: Biostats 3110B or Biostats 9509A
Course Weight: 0.25 credits
This course provides a conceptual knowledge basis for design of randomized controlled trials with a pragmatic purpose: i.e., providing evidence to support clinical, public health or health system decision-makers to choose between alternative interventions. Students will learn how to increase the relevance to decision makers by inclusive selection of participants and setting, usual care comparators, and simplified data collection and organization of the trial. The course approach is practical, illustrating each concept with a published, real-world trial. Students may choose to continue their studies of Randomized Trials by enrolling in the second half of this course Epidemiology 9568T: Randomized Trials: Analysis.
Course Weight: 0.25 credits
This course provides a conceptual knowledge basis for design of randomized controlled trials with a pragmatic purpose: i.e., providing evidence to support clinical, public health or health system decision-makers to choose between alternative interventions. Students will learn how to increase the relevance to decision makers by inclusive selection of participants and setting, usual care comparators, and simplified data collection and organization of the trial. The course approach is practical, illustrating each concept with a published, real-world trial. Students may choose to continue their studies of Randomized Trials by enrolling in the second half of this course Epidemiology 9568T: Randomized Trials: Analysis.
Epidemiology 9568T: Randomized Trials: Analysis
Prerequisite: Epidemiology 9566S
Co-requisite: Biostats 3110B or Biostats 9509A
Course Weight: 0.25 credits
This course provides comprehensive coverage of the issues involved in the analysis of data from randomized trials including cross-over trials, cluster randomization trials and trials where patient reported outcomes are of particular importance. Attention will also be given to survival analysis and repeated measures.
Co-requisite: Biostats 3110B or Biostats 9509A
Course Weight: 0.25 credits
This course provides comprehensive coverage of the issues involved in the analysis of data from randomized trials including cross-over trials, cluster randomization trials and trials where patient reported outcomes are of particular importance. Attention will also be given to survival analysis and repeated measures.
Epidemiology 9572Q: Introduction to Health Economics
Course Weight: 0.25 credits
This course will focus on the concepts and methods relevant to understanding health policy decisions from an economic perspective. It will cover the following topics: microeconomic tools for health economics, demand for and supply of healthcare, market failure in the health sector, and demand for health insurance.
This course will focus on the concepts and methods relevant to understanding health policy decisions from an economic perspective. It will cover the following topics: microeconomic tools for health economics, demand for and supply of healthcare, market failure in the health sector, and demand for health insurance.
Epidemiology 9580S: Systematic Reviews
Course Weight: 0.25 credits
Systematic reviews form the core of evidence-based decision-making in health care and are based on reliable syntheses of research information. This course will cover the theory and rationale behind systematic reviews, discuss strengths and limitations of the methods, and give step-by-step guidance on how to do a systematic review.
Systematic reviews form the core of evidence-based decision-making in health care and are based on reliable syntheses of research information. This course will cover the theory and rationale behind systematic reviews, discuss strengths and limitations of the methods, and give step-by-step guidance on how to do a systematic review.
Epidemiology 9582T: Meta-Analysis
Prerequisite: Epidemiology 9580S
Course Weight: 0.25 credits
This course is designed to provide details of the process of conducting a meta-analysis and to discuss strengths and limitations of the methods. Familiarity with systematic review methods is required for this course.
Course Weight: 0.25 credits
This course is designed to provide details of the process of conducting a meta-analysis and to discuss strengths and limitations of the methods. Familiarity with systematic review methods is required for this course.
Epidemiology 9590T: Measurement in Epidemiology
Prerequisite: Epidemiology 9551A and one of Biostatistics 9509A or Biostatistics 9510A
Course Weight: 0.25 credits
This course will focus on methodological issues related to the measurement of exposures, outcomes, and other relevant covariates in epidemiologic research. Topics to be covered include scale development, assessment of reliability and validity, and factor analysis. Students will learn how to choose an instrument when designing an epidemiologic study and understand the implications of measurement error on their analyses.
Course Weight: 0.25 credits
This course will focus on methodological issues related to the measurement of exposures, outcomes, and other relevant covariates in epidemiologic research. Topics to be covered include scale development, assessment of reliability and validity, and factor analysis. Students will learn how to choose an instrument when designing an epidemiologic study and understand the implications of measurement error on their analyses.
Epidemiology 9690R: Advanced Topics in Epidemiology and Biostatistics
Prerequisites: Biostatistics 9681Q and restricted to PhD students
Course Weight: 0.25 credits
This course is designed to give students pursuing a Ph.D. in either epidemiology or biostatistics a synergized introduction to advanced theoretical concepts and emerging methods.
Course Weight: 0.25 credits
This course is designed to give students pursuing a Ph.D. in either epidemiology or biostatistics a synergized introduction to advanced theoretical concepts and emerging methods.
