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Michael Law
Interrupted time series analysis and regression discontinuity designs are two of the most rigorous ways to evaluate policies with routinely collected data. ITSx comprehensively introduces analysts to interrupted time series analysis (ITS) and regression discontinuity designs (RD) from start to finish, including selection and setup of data sources, statistical analysis, interpretation and presentation, and identification of potential pitfalls.
Read more
Interrupted time series analysis and regression discontinuity designs are two of the most rigorous ways to evaluate policies with routinely collected data. ITSx comprehensively introduces analysts to interrupted time series analysis (ITS) and regression discontinuity designs (RD) from start to finish, including selection and setup of data sources, statistical analysis, interpretation and presentation, and identification of potential pitfalls.
Read more
Interrupted time series analysis and regression discontinuity designs are two of the most rigorous ways to evaluate policies with routinely collected data. ITSx comprehensively introduces analysts to interrupted time series analysis (ITS) and regression discontinuity designs (RD) from start to finish, including selection and setup of data sources, statistical analysis, interpretation and presentation, and identification of potential pitfalls.
At the conclusion of the course, students will have all the tools necessary to propose, conduct and correctly interpret an analysis using ITS and RD approaches. This will help them position themselves as a go-to person within their company, government department, or academic department as the technical expert on this topic.
ITS and RD designs avoid many of the pitfalls associated with other techniques. As a result of their analytic strength, the use of ITS and RD approaches has been rapidly increasing over the past decade. These studies have cut across the social sciences, including:
- Studying the effect of traffic speed zones on mortality
- Quantifying the impact of incentive payments to workers on productivity
- Assessing whether alcohol policies reduce suicide
- Measuring the impact of incentive payments to physicians on quality of care
- Determining whether the use of HPV vaccination influences adolescent sexual behavior
Register for this course and see more details by visiting:
OpenCourser.com/course/s159a9/policy
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What's inside
Learning objectives
- The strengths and drawbacks of its and rd studies
- Data requirements, setup, and statistical modelling
- Interpretation of results for non-technical audiences
- Production of compelling figures
- The strengths and drawbacks of its and rd studies
- Data requirements, setup, and statistical modelling
- Interpretation of results for non-technical audiences
- Production of compelling figures
Syllabus
Week 1: Course overview
Introduction to ITS and RD designs
Assumptions and potential biases
Data sources and requirements
Read more
Syllabus
Week 1: Course overview
Introduction to ITS and RD designs
Assumptions and potential biases
Data sources and requirements
Read more
Example studies
An introduction to R (optional)
Week 2: Single series ITS
Data setup and adding variables
Model selection
Addressing autocorrelation
Graphical presentation
Week 3: ITS with a control group
Data setup
Adding a control to the model
Predicting policy impacts
Week 4: Extensions
Advanced modeling issues in ITS and RD
Non-linear Trends · Differencing
“Wild” Points and Transition periods
Adding a Second Intervention
Week 5: Regression Discontinuities and Wrap-up
Regression Discontinuities
Any Remaining Questions
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Employs a practical approach starting with data preparation, modeling, and communicating results
Geared towards students with intermediate statistical knowledge seeking to validate the outcomes of policies
Taught by instructors with notable experience in interrupted time series analysis and regression discontinuity design
Examines the practical applications of interrupted time series analysis and regression discontinuity design in various fields, including healthcare, education, and policy analysis
Provides hands-on experience with real-world datasets, enhancing the practical value of the course
May require additional preparation for learners without prior experience in statistical modeling
Save this course
Save Policy Analysis Using Interrupted Time Series to your list so you can find it easily later:
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Reviews summary
Highly rated: time series analysis policy
According to students, Policy Analysis Using Interrupted Time Series is a well-received course. Positive reviews largely mention the course's interesting and engaging content.
The course material is interesting.
"I'm just testing to see if this is working, if it works, great. Interesting site. Very interesting."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Policy Analysis Using Interrupted Time Series with these
activities:
Review the concept of causality
Show steps
Provides a foundation for understanding the causal claims that can be made using ITS and RD designs.
Show steps
-
Read the chapters on causality in the assigned textbooks
Review basic statistics
Show steps
Review the fundamental concepts of statistics to ensure a solid foundation for understanding interrupted time series analysis and regression discontinuity designs.
Browse courses on
Descriptive Statistics
Show steps
-
Review notes or textbooks on basic statistical concepts.
-
Solve practice problems to reinforce understanding.
Follow the RMarkdown tutorial on interrupted time series analysis
Show steps
Provides hands-on experience with interrupted time series analysis using the R programming language.
Show steps
-
Install the necessary R packages
-
Load the data and visualize it
-
Fit an interrupted time series model
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Form a study group
Show steps
Join or create a study group to discuss course concepts, work through practice problems, and learn from each other's perspectives, reinforcing your understanding and enhancing your learning experience.
Show steps
-
Find classmates who are interested in forming a study group.
-
Set up regular meeting times and locations.
-
Prepare materials for each session, such as questions, practice problems, or summaries.
-
Actively participate in discussions and share your insights.
Conduct regression discontinuity analysis on simulated data
Show steps
Strengthens understanding of regression discontinuity design in the context of simulated datasets.
Show steps
-
Simulate data with a discontinuity
-
Fit a regression discontinuity model
-
Interpret the results
Data visualization practice
Show steps
Practice creating different types of data visualizations to solidify your understanding of the different techniques and when to use them.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset and explore it.
-
Select the appropriate type of visualization for the data.
-
Create the visualization using a software tool.
-
Interpret the visualization and draw conclusions.
Solve practice problems
Show steps
Work through practice problems on interrupted time series analysis and regression discontinuity designs to solidify your understanding of the statistical techniques and their applications.
Browse courses on
Statistical Modeling
Show steps
-
Find practice problems from textbooks, online resources, or your instructor.
-
Solve the problems independently.
-
Check your answers and identify areas for improvement.
Join a peer discussion group and present your ITS or RD analysis
Show steps
Provides opportunities for presenting and discussing research findings with peers, fostering a sense of community and scientific discourse.
Show steps
-
Find a peer group
-
Prepare your presentation
-
Present your analysis
Write a paper on the results of an ITS or RD analysis
Show steps
Develops skills in writing scientific papers and communicating research findings.
Show steps
-
Choose a topic
-
Gather and analyze data
-
Write a draft
Write a blog post on ITS and RD
Show steps
Create a blog post that explains the concepts of interrupted time series analysis and regression discontinuity designs to a non-technical audience, showcasing your understanding and ability to communicate complex ideas clearly.
Show steps
-
Research and gather information on ITS and RD.
-
Write an outline for your blog post.
-
Draft the content, explaining the concepts in a clear and engaging manner.
-
Edit and proofread your blog post.
-
Publish your blog post.
Conduct a mock analysis
Show steps
Apply your understanding of ITS and RD by conducting a mock analysis on a real-world dataset, providing you with hands-on experience and a deeper understanding of the practical applications of these techniques.
Show steps
-
Identify a suitable dataset for analysis.
-
Choose the appropriate ITS or RD design for the analysis.
-
Conduct the analysis using statistical software.
-
Interpret the results and draw conclusions.
-
Create a report summarizing your findings.
Review the concept of causality
Show steps
Provides a foundation for understanding the causal claims that can be made using ITS and RD designs.
Show steps
Show steps
Show steps
- Read the chapters on causality in the assigned textbooks
Review basic statistics
Show steps
Review the fundamental concepts of statistics to ensure a solid foundation for understanding interrupted time series analysis and regression discontinuity designs.
Browse courses on
Descriptive Statistics
Show steps
Show steps
Show steps
- Review notes or textbooks on basic statistical concepts.
- Solve practice problems to reinforce understanding.
Follow the RMarkdown tutorial on interrupted time series analysis
Show steps
Provides hands-on experience with interrupted time series analysis using the R programming language.
Show steps
Show steps
Show steps
- Install the necessary R packages
- Load the data and visualize it
- Fit an interrupted time series model
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Form a study group
Show steps
Join or create a study group to discuss course concepts, work through practice problems, and learn from each other's perspectives, reinforcing your understanding and enhancing your learning experience.
Show steps
Show steps
Show steps
- Find classmates who are interested in forming a study group.
- Set up regular meeting times and locations.
- Prepare materials for each session, such as questions, practice problems, or summaries.
- Actively participate in discussions and share your insights.
Conduct regression discontinuity analysis on simulated data
Show steps
Strengthens understanding of regression discontinuity design in the context of simulated datasets.
Show steps
Show steps
Show steps
- Simulate data with a discontinuity
- Fit a regression discontinuity model
- Interpret the results
Data visualization practice
Show steps
Practice creating different types of data visualizations to solidify your understanding of the different techniques and when to use them.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset and explore it.
- Select the appropriate type of visualization for the data.
- Create the visualization using a software tool.
- Interpret the visualization and draw conclusions.
Solve practice problems
Show steps
Work through practice problems on interrupted time series analysis and regression discontinuity designs to solidify your understanding of the statistical techniques and their applications.
Browse courses on
Statistical Modeling
Show steps
Show steps
Show steps
- Find practice problems from textbooks, online resources, or your instructor.
- Solve the problems independently.
- Check your answers and identify areas for improvement.
Join a peer discussion group and present your ITS or RD analysis
Show steps
Provides opportunities for presenting and discussing research findings with peers, fostering a sense of community and scientific discourse.
Show steps
Show steps
Show steps
- Find a peer group
- Prepare your presentation
- Present your analysis
Write a paper on the results of an ITS or RD analysis
Show steps
Develops skills in writing scientific papers and communicating research findings.
Show steps
Show steps
Show steps
- Choose a topic
- Gather and analyze data
- Write a draft
Write a blog post on ITS and RD
Show steps
Create a blog post that explains the concepts of interrupted time series analysis and regression discontinuity designs to a non-technical audience, showcasing your understanding and ability to communicate complex ideas clearly.
Show steps
Show steps
Show steps
- Research and gather information on ITS and RD.
- Write an outline for your blog post.
- Draft the content, explaining the concepts in a clear and engaging manner.
- Edit and proofread your blog post.
- Publish your blog post.
Conduct a mock analysis
Show steps
Apply your understanding of ITS and RD by conducting a mock analysis on a real-world dataset, providing you with hands-on experience and a deeper understanding of the practical applications of these techniques.
Show steps
Show steps
Show steps
- Identify a suitable dataset for analysis.
- Choose the appropriate ITS or RD design for the analysis.
- Conduct the analysis using statistical software.
- Interpret the results and draw conclusions.
- Create a report summarizing your findings.
Career center
Learners who complete Policy Analysis Using Interrupted Time Series will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A data scientist is a professional who uses data to solve complex problems. They use data analysis techniques to identify trends and patterns in data. The Policy Analysis Using Interrupted Time Series course can be useful for data scientists because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of policies. This course can help data scientists to develop the skills they need to conduct rigorous research on the effectiveness of policies.
Biostatistician
Biostatistician
A biostatistician is a statistician who applies statistical methods to the study of health data. They work with researchers to design studies, analyze data, and interpret results. The Policy Analysis Using Interrupted Time Series course can be useful for biostatisticians because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of health care policies. This course can help biostatisticians to develop the skills they need to conduct rigorous research on the effectiveness of health care interventions.
Health Economist
Health Economist
A health economist is an economist who applies economic principles to the study of health care. They use data analysis to evaluate the cost-effectiveness of health care interventions, such as new drugs and treatments. The Policy Analysis Using Interrupted Time Series course can be useful for health economists because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of health care policies. This course can help health economists to develop the skills they need to conduct rigorous research on the cost-effectiveness of health care interventions.
Statistician
Statistician
A statistician is a professional who uses data to solve problems. They use data analysis techniques to identify trends, patterns, and relationships in data. The Policy Analysis Using Interrupted Time Series course can be useful for statisticians because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of policies. This course can help statisticians to develop the skills they need to conduct rigorous research on the effectiveness of policies.
Public Policy Analyst
Public Policy Analyst
A public policy analyst is a professional who studies public policy. They use data analysis techniques to evaluate the impact of public policies. The Policy Analysis Using Interrupted Time Series course can be useful for public policy analysts because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of public policies. This course can help public policy analysts to develop the skills they need to conduct rigorous research on the effectiveness of public policies.
Epidemiologist
Epidemiologist
An epidemiologist is a public health professional who studies the causes of disease and other health problems in populations. They use data analysis to track health trends, identify risk factors, and evaluate the effectiveness of public health interventions. The Policy Analysis Using Interrupted Time Series course can be useful for epidemiologists because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of public health policies. This course can help epidemiologists to develop the skills they need to conduct rigorous research on the causes and prevention of disease.
Economist
Economist
An economist is a professional who studies the economy. They use data analysis techniques to identify trends and patterns in the economy. The Policy Analysis Using Interrupted Time Series course can be useful for economists because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of economic policies. This course can help economists to develop the skills they need to conduct rigorous research on the effectiveness of economic policies.
Research Analyst
Research Analyst
A research analyst is a professional who conducts research on a variety of topics. They use data analysis techniques to identify trends and patterns in data. The Policy Analysis Using Interrupted Time Series course can be useful for research analysts because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of policies. This course can help research analysts to develop the skills they need to conduct rigorous research on the effectiveness of policies.
Data Analyst
Data Analyst
A data analyst is a professional who uses data to solve business problems. They use data analysis techniques to identify trends, patterns, and relationships in data. The Policy Analysis Using Interrupted Time Series course can be useful for data analysts because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of business decisions. This course can help data analysts to develop the skills they need to conduct rigorous research on the effectiveness of business decisions.
Market Researcher
Market Researcher
A market researcher is a professional who studies consumer behavior. They use data analysis techniques to identify trends and patterns in consumer behavior. The Policy Analysis Using Interrupted Time Series course can be useful for market researchers because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of marketing campaigns. This course can help market researchers to develop the skills they need to conduct rigorous research on the effectiveness of marketing campaigns.
Social Scientist
Social Scientist
A social scientist is a professional who studies human behavior and society. They use data analysis techniques to identify trends and patterns in human behavior. The Policy Analysis Using Interrupted Time Series course can be useful for social scientists because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of social policies. This course can help social scientists to develop the skills they need to conduct rigorous research on the effectiveness of social policies.
Consultant
Consultant
A consultant is a professional who provides advice to businesses and organizations. They use data analysis techniques to identify trends and patterns in data. The Policy Analysis Using Interrupted Time Series course can be useful for consultants because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of business decisions. This course can help consultants to develop the skills they need to conduct rigorous research on the effectiveness of business decisions.
Product Manager
Product Manager
A product manager is a professional who manages the development and launch of products. They use data analysis techniques to identify trends and patterns in data. The Policy Analysis Using Interrupted Time Series course may be useful for product managers because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of product launches. This course can help product managers to develop the skills they need to conduct rigorous research on the effectiveness of product launches.
Business Analyst
Business Analyst
A business analyst is a professional who helps businesses improve their performance. They use data analysis techniques to identify trends and patterns in data. The Policy Analysis Using Interrupted Time Series course may be useful for business analysts because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of business decisions. This course can help business analysts to develop the skills they need to conduct rigorous research on the effectiveness of business decisions.
Software Engineer
Software Engineer
A software engineer is a professional who designs and develops software. They use data analysis techniques to identify trends and patterns in data. The Policy Analysis Using Interrupted Time Series course may be useful for software engineers because it provides training in the design and analysis of interrupted time series studies, which are often used to evaluate the impact of software updates. This course can help software engineers to develop the skills they need to conduct rigorous research on the effectiveness of software updates.
For more career information including salaries, visit:
OpenCourser.com/course/s159a9/policy
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Policy Analysis Using Interrupted Time Series.
Provides a clear and concise introduction to causal inference, including topics such as confounding, selection bias, and instrumental variables. It valuable resource for researchers and practitioners who want to learn more about this important topic.
Save
Provides a comprehensive introduction to time series analysis, including topics such as forecasting, seasonality, and trend analysis. It valuable reference for researchers and practitioners who want to learn more about these methods.
Save
Provides a comprehensive introduction to machine learning for time series forecasting, including topics such as data preparation, model selection, and evaluation. It valuable reference for researchers and practitioners who want to learn more about these methods.
Provides a comprehensive introduction to time series analysis, including topics such as stationarity, seasonality, and forecasting. It valuable reference for researchers and practitioners who want to learn more about this area of statistics.
Provides a comprehensive introduction to the econometrics of time series, including topics such as stationarity, seasonality, and forecasting. It valuable reference for researchers and practitioners who want to learn more about this area of statistics.
Provides a practical introduction to time series analysis, including topics such as forecasting, seasonality, and trend analysis. It valuable reference for researchers and practitioners who want to learn more about these methods.
Save
Provides a comprehensive introduction to linear models, including topics such as regression analysis, ANOVA, and multivariate analysis. It valuable reference for researchers and practitioners who want to learn more about these methods.
Provides a comprehensive introduction to regression analysis, including topics such as linear regression, logistic regression, and multilevel models. It valuable reference for researchers and practitioners who want to learn more about these methods.
Provides a comprehensive introduction to econometrics, including topics such as regression analysis, time series analysis, and forecasting. It valuable reference for researchers and practitioners who want to learn more about these methods.
Provides a comprehensive overview of statistical methods used in applied research, including topics such as hypothesis testing, regression analysis, and analysis of variance. It valuable reference for researchers and practitioners who want to learn more about these methods.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/s159a9/policy
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Effort
6 to 10 hours per week for 5 weeks
Level
Intermediate
Via
edX
Institution
University of British Columbia
Instructor
Michael Law
Language
English
Transcript
English
Good to know
Employs a practical approach starting with data preparation, modeling, and communicating results
Geared towards students with intermediate statistical knowledge seeking to validate the outcomes of policies
Taught by instructors with notable experience in interrupted time series analysis and regression discontinuity design
Examines the practical applications of interrupted time series analysis and regression discontinuity design in various fields, including healthcare, education, and policy analysis
Provides hands-on experience with real-world datasets, enhancing the practical value of the course
May require additional preparation for learners without prior experience in statistical modeling
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