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Introduction to Propensity Score Analysis with R workshop

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Learn how to use propensity score analysis in R! Join our workshop on Introduction to Propensity Score Analysis with R which is a part of our workshops for Ukraine series. 


Here’s some more info: 

Title: Introduction to Propensity Score Analysis with R

Date: Thursday, July 6th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone)

Speaker: Dr. Jason Bryer is currently an Assistant Professor and Associate Director in the Data Science and Information Systems department at the City University of New York. He is currently the Principal Investigator of the FIPSE ($3 million #P116F150077) and IES funded ($3.8 million R305A210269) Diagnostic Assessment and Achievement of College Skills (DAACS), which is a suite of technological and social supports designed to optimize student learning. Dr. Bryer’s other research interests include quasi-experimental designs with an emphasis on propensity score analysis, data systems to support formative assessment, and the use of open source software for conducting reproducible research. He is the author of over a dozen R packages, including three related to conducting propensity score analyses. When not crunching numbers, Jason is a wedding photographer and proud dad to three boys.

Description: The use of propensity score methods (Rosenbaum & Rubin, 1983) for estimating causal effects in observational studies or certain kinds of quasi-experiments has been increasing in the social sciences (Thoemmes & Kim, 2011) and in medical research (Austin, 2008) in the last decade. Propensity score analysis (PSA) attempts to adjust selection bias that occurs due to the lack of randomization. Analysis is typically conducted in two phases where in phase I, the probability of placement in the treatment is estimated to identify matched pairs or clusters so that in phase II, comparisons on the dependent variable can be made between matched pairs or within clusters. R (R Core Team, 2012) is ideal for conducting PSA given its wide availability of the most current statistical methods vis-à-vis add-on packages as well as its superior graphics capabilities.

This workshop will provide participants with a theoretical overview of propensity score methods as well as illustrations and discussion of PSA applications. Methods used in phase I of PSA (i.e. models or methods for estimating propensity scores) include logistic regression, classification trees, and matching. Discussions on appropriate comparisons and estimations of effect size and confidence intervals in phase II will also be covered. The use of graphics for diagnosing covariate balance as well as summarizing overall results will be emphasized.


Minimal registration fee: 20 euro (or 20 USD or 800 UAH)

How can I register?


If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.


How can I sponsor a student?


If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).


You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.


Looking forward to seeing you during the workshop!














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