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Policy Analysis: Interrupted Time Series Methods

Master interrupted time series analysis and regression discontinuity designs for rigorous policy evaluation using R programming.

Master interrupted time series analysis and regression discontinuity designs for rigorous policy evaluation using R programming.

This comprehensive course teaches advanced methods for policy evaluation using interrupted time series analysis (ITS) and regression discontinuity designs (RD). Led by UBC experts, participants learn to conduct thorough policy analyses from data selection to result interpretation. The curriculum covers statistical modeling, data visualization, and practical applications across social sciences. Students gain expertise in R programming for time series analysis, preparing them to become technical experts in their organizations.

4.6

(5 ratings)

14,884 already enrolled

Instructors:

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Policy Analysis: Interrupted Time Series Methods

This course includes

5 Weeks

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

4,199

What you'll learn

  • Master interrupted time series analysis and regression discontinuity designs

  • Develop expertise in data preparation and statistical modeling using R

  • Learn to interpret and present results for non-technical audiences

  • Create compelling data visualizations for policy analysis

  • Identify and address potential biases and methodological issues

Skills you'll gain

Time Series Analysis
Policy Evaluation
Statistical Modeling
R Programming
Data Visualization
Regression Analysis
Research Methods
Data Analysis
Policy Impact Assessment

This course includes:

PreRecorded video

Graded assignments, exams

Access on Mobile, Tablet, Desktop

Limited Access access

Shareable certificate

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There are 5 modules in this course

This advanced course focuses on two rigorous methods for policy evaluation: interrupted time series analysis (ITS) and regression discontinuity designs (RD). The curriculum provides comprehensive training in selecting and preparing data sources, conducting statistical analyses, interpreting results, and identifying potential methodological issues. Students learn to use R programming for complex time series analysis and create compelling visualizations. The course emphasizes practical applications across various social science domains, from healthcare policy to economic interventions.

Course overview

Module 1 · 8 Hours to complete

Single series ITS

Module 2 · 8 Hours to complete

ITS with a control group

Module 3 · 8 Hours to complete

Extensions

Module 4 · 8 Hours to complete

Regression Discontinuities and Wrap-up

Module 5 · 8 Hours to complete

Fee Structure

Instructor

Michael Law
Michael Law

1 Course

Accomplished Health Policy Expert and Researcher at UBC

Dr. Michael Law is a Professor and Canada Research Chair in Access to Medicines at the University of British Columbia's School of Population and Public Health, where his groundbreaking research focuses on pharmaceutical policy and access to medicines. After completing his PhD in Health Policy from Harvard University and a post-doctoral fellowship at Harvard Medical School, he has built an impressive career combining academic excellence with practical policy impact. His research portfolio, supported by over $2.5 million in funding including CIHR grants, spans multiple countries including Canada, Rwanda, Uganda, Namibia, and Colombia. A graduate of the London School of Economics (MSc) and McMaster University's Arts & Sciences Program (BA&Sc), Law has published extensively in leading medical journals, with his work featured in prestigious media outlets like New Scientist, Forbes, The New York Times, and USA Today. His achievements include the Labelle Lectureship at McMaster University, the 2011 Paper of the Year Award from the Canadian Institute for Health Services and Policy Research, a CIHR New Investigator Award, and a Michael Smith Foundation for Health Research Scholar Award. At UBC, he excels in teaching pharmaceutical policy, health insurance, and healthcare systems, earning the Cortland MacKenzie Teaching Prize for outstanding teaching evaluations in the School of Population and Public Health.

Policy Analysis: Interrupted Time Series Methods

This course includes

5 Weeks

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

4,199

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.6 course rating

5 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.