Propensity Score Analysis: Advanced - Online Course
A 3-Day Livestream Seminar Taught by
Shenyang Guo10:00am-12:30pm (convert to your local time)
1:30pm-3:30pm
Propensity score analysis is a relatively new and innovative class of statistical methods that has proven useful for evaluating the effects of treatments or interventions when using nonexperimental or observational data. This seminar is a follow-up of Propensity Score Analysis: Basics. By taking this seminar, you will learn advanced methods of propensity score analysis, including kernel-based matching, propensity score subclassification (i.e., running PSA in conjunction with survival analysis or other outcome models), propensity score analysis of categorical or continuous treatments (i.e., dosage analysis), and Rosenbaum sensitivity analysis of hidden selections.
Starting April 4, we are offering this seminar as a 3-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.
*We understand that finding time to participate in livestream courses can be difficult. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.
Closed captioning is available for all live and recorded sessions. Live captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.
More details about the course content
This seminar will focus on the following advanced methods of propensity score analysis:
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- The kernel-based matching developed by Heckman et al.
- Propensity score subclassification (i.e., running PSA in conjunction with survival analysis or other outcome models).
- Propensity score dosage analysis, including Imbens’s model for a categorical treatment condition and Hirano and Imbens’s generalized propensity score method for a continuous treatment condition.
- Rosenbaum sensitivity analysis of hidden selections.
This seminar will focus on the following advanced methods of propensity score analysis:
-
- The kernel-based matching developed by Heckman et al.
- Propensity score subclassification (i.e., running PSA in conjunction with survival analysis or other outcome models).
- Propensity score dosage analysis, including Imbens’s model for a categorical treatment condition and Hirano and Imbens’s generalized propensity score method for a continuous treatment condition.
- Rosenbaum sensitivity analysis of hidden selections.
Computing
The seminar uses Stata and R software packages to demonstrate the implementation of propensity score analysis. All Stata and R syntax files and illustrative data can be downloaded at the Propensity Score Analysis Support Site. You are strongly encouraged to use a computer with Stata or R installed. To follow along with the course exercises, you should be able to perform basic data manipulation and analyses in Stata or R.
If you’d like to use Stata for this course but don’t yet have much experience with that package, we recommend following along with a “getting started” video like the one here before the seminar begins.
Seminar participants who are not yet ready to purchase Stata could take advantage of StataCorp’s free 30-day evaluation offer or their 30-day software return policy.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent on-line resources for building your R skills.
The seminar uses Stata and R software packages to demonstrate the implementation of propensity score analysis. All Stata and R syntax files and illustrative data can be downloaded at the Propensity Score Analysis Support Site. You are strongly encouraged to use a computer with Stata or R installed. To follow along with the course exercises, you should be able to perform basic data manipulation and analyses in Stata or R.
If you’d like to use Stata for this course but don’t yet have much experience with that package, we recommend following along with a “getting started” video like the one here before the seminar begins.
Seminar participants who are not yet ready to purchase Stata could take advantage of StataCorp’s free 30-day evaluation offer or their 30-day software return policy.
If you’d like to use R for this course but don’t yet have much experience with that package, here are some excellent on-line resources for building your R skills.
Who should register?
This seminar assumes that you have already taken Propensity Score Analysis: Basics or have equivalent knowledge. Researchers who wish to learn advanced topics of PSA may consider registering. The seminar will be helpful to researchers who are engaged in intervention research, program evaluation, or more generally causal inference, when their data were not generated by a randomized clinical trial. The prerequisite for taking this seminar is knowledge of multiple regression analysis. Researchers from economics, public health, epidemiology, psychology, sociology, social work, medical research, education, and similar disciplines may consider participating.
This seminar assumes that you have already taken Propensity Score Analysis: Basics or have equivalent knowledge. Researchers who wish to learn advanced topics of PSA may consider registering. The seminar will be helpful to researchers who are engaged in intervention research, program evaluation, or more generally causal inference, when their data were not generated by a randomized clinical trial. The prerequisite for taking this seminar is knowledge of multiple regression analysis. Researchers from economics, public health, epidemiology, psychology, sociology, social work, medical research, education, and similar disciplines may consider participating.
Seminar outline
Day 1:
-
- Kernel-based matching
- Propensity score subclassification (running PSA in conjunction with survival analysis or other outcome models)
Day 2:
-
- Propensity score dosage analysis for a categorical treatment condition
- Propensity score dosage analysis for a continuous treatment condition
Day 3:
-
- Rosenbaum sensitivity analysis of hidden selections
- Debates and directions of future development
Day 1:
-
- Kernel-based matching
- Propensity score subclassification (running PSA in conjunction with survival analysis or other outcome models)
Day 2:
-
- Propensity score dosage analysis for a categorical treatment condition
- Propensity score dosage analysis for a continuous treatment condition
Day 3:
-
- Rosenbaum sensitivity analysis of hidden selections
- Debates and directions of future development
Payment information
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.