Course Website Locator: epi289-01

Harvard School of Public Health

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Spring 1 2010

M. Hernan
2.5 credits
Lectures, labs. Two 2-hour sessions each week, one 2-hour lab each week.

EPI289 describes models for causal inference, their assumptions, and their practical application to epidemiologic data. The course covers propensity score methods, the parametric g-formula, inverse probability weighting of marginal structural models, g-estimation of nested structural models, and instrumental variable methods. The course also introduces models for causal inference in the presence of time-varying exposures, which will be extensively studied in EPI207. EPI289 is designed to be taken after EPI201/EPI202. The epidemiologic concepts and methods studied in EPI201/202 will be reformulated within a modeling framework in EPI289. Familiarity with the SAS language is strongly recommended.

Course Note: Wednesday lab required; no auditors.

Spring 1 2009

M. Hernan
2.5 credits
Lectures, labs. Two 2-hour sessions each week, one 2-hour lab each week.

EPI289 describes models for causal inference, their assumptions, and their practical application to epidemiologic data. The course introduces ropensity score methods, the parametric g-formula, inverse probability weighting of marginal structural models, g-estimation of nested structural models, and instrumental variable methods. The course also introduces methods for causal inference in the presence of time-varying exposures, and for infectious disease epidemiology, which will be extensively studied in EPI207 and EPI260/EPI501, respectively. EPI289 is designed to be taken after EPI201/EPI202 and concurrently with EPI204. The epidemiologic concepts and methods studied in EPI201/202 will be reformulated within a modeling framework in EPI289, and the statistical models described in EPI204 will be used throughout EPI289. Some familiarity with the SAS anguage is recommended.

Course Note: Wednesday lab required; no auditors.

Spring 1 2008

Dr. M. Hernan
2.5 credits
Lectures, case studies, lab. Two 2-hour lectures and one 2-hour lab each week.

Causal inference from observational data is a key task of epidemiology and of allied sciences such as sociology, education, behavioral sciences, demography, economics, health services research, etc. These disciplines share a methodological framework for causal inference that has been developed over the last decades.

EPI289 presents this unifying causal theory and shows how epidemiologic concepts and methods introduced in EPI201 and EPI202 can be understood within this general framework. The course emphasizes conceptualization but also introduces statistical models and methods for time-varying exposures, which will be extensively studied in EPI204 and EPI207.
Course note: EPI202 required; Wednesday lab required at 1:30 to 3:20 or 3:30 to 5:20 pm; ordinal grading option only. (5.06)

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.

Spring 1 2007

Dr. M. Hernan
2.5 credits
Lectures, case studies, lab. Two 2-hour lectures and one 2-hour lab each week.

Causal inference from observational data is a key task of epidemiology and of allied sciences such as sociology, education, behavioral sciences, demography, economics, health services research, etc. These disciplines share a methodological framework for causal inference that has been developed over the last decades.

EPI289 presents this unifying causal theory and shows how epidemiologic concepts and methods introduced in EPI201 and EPI202 can be understood within this general framework. The course emphasizes conceptualization but also introduces statistical models and methods for time-varying exposures, which will be extensively studied in EPI204 and EPI207.
Course note: EPI202 required; Wednesday lab required at 1:30 to 3:20 or 3:30 to 5:20 pm; ordinal grading option only. (5.06)

Course evaluations are an important method for feedback on the quality of course offerings. The submission of a course evaluation is a requirement for this course. Your grade for the course will be made available only after you have submitted responses to at least the first three questions of the on-line evaluation for this course.

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