Course Website Locator: epi271-01

Harvard School of Public Health

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Winter 2010

Dr. T. Kurth , Dr. J. D. Seeger
1.25 Credits
Lectures, Computer Lab. Five 2-hour lectures and four 2-hour computer lab sessions

This course introduces basic and advanced theory underlying propensity score analyses and provides practical insights into the conduct of studies employing the method. Course readings will include propensity score theory as well as applications. Lectures are complemented by computer lab sessions devoted to the mechanics of estimating and using the propensity score as a tool to control for confounding in observational research. Students should have knowledge in multivariable modeling approaches. A course project will involve the application of propensity scores to a data set.
Course Activities: Lectures, readings, homeworks, computer labs, participation, project.
Course Notes: BIO210 or equivalent or EPI204 or equivalent required; instructor's signature required. Course meeting dates: TBA

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.

Winter 2009

Dr. T. Kurth , Dr. J. D. Seeger
1.25 Credits
Lectures, Computer Lab. Five 2-hour lectures and four 2-hour computer lab sessions

This course introduces basic and advanced theory underlying propensity score analyses and provides practical insights into the conduct of studies employing the method. Course readings will include propensity score theory as well as applications. Lectures are complemented by computer lab sessions devoted to the mechanics of estimating and using the propensity score as a tool to control for confounding in observational research. Students should have knowledge in multivariable modeling approaches. A course project will involve the application of propensity scores to a data set.
Course Activities: Lectures, readings, homeworks, computer labs, participation, project.
Course Notes: BIO210 or equivalent or EPI204 or equivalent required; instructor's signature required. Course meeting dates: January 5-9 from 8:30 am to 10:20 am, labs from 10:30 am to 12:30 pm.

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.

Winter 2008

Dr. T. Kurth , Dr. J. D. Seeger
1.25 Credits
Lectures, Computer Lab. Five 2-hour lectures and four 2-hour computer lab sessions

This course introduces basic and advanced theory underlying propensity score analyses and provides practical insights into the conduct of studies employing the method. Course readings will include propensity score theory as well as applications. Lectures are complemented by computer lab sessions devoted to the mechanics of estimating and using the propensity score as a tool to control for confounding in observational research. Students should have knowledge in multivariable modeling approaches. A course project will involve the application of propensity scores to a data set.
Course Activities: Lectures, readings, homeworks, computer labs, participation, project.
Course Notes: BIO210 or equivalent or EPI204 or equivalent required; instructor's signature required. Course meeting dates: January 7-11 from 8:30 am to 10:20 am, labs from 10:30 am to 12:30 pm.

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.

Winter 2007

Dr. T. Kurth , Dr. J. D. Seeger
1.25 Credits
Lectures, Computer Lab. Five 2-hour lectures and four 2-hour computer lab sessions

This course introduces basic and advanced theory underlying propensity score analyses and provides practical insights into the conduct of studies employing the method. Course readings will include propensity score theory as well as applications. Lectures are complemented by computer lab sessions devoted to the mechanics of estimating and using the propensity score as a tool to control for confounding in observational research. Students should have knowledge in multivariable modeling approaches. A course project will involve the application of propensity scores to a data set.
Course Activities: Lectures, readings, homeworks, computer labs, participation, project.
Course Notes: BIO210 or equivalent or EPI204 or equivalent required; instructor's signature required. Course meeting dates TBA, from 8:30 am to 10:20 am, labs from 10:30 am to 12:30 pm. (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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