Inverse Probability Weighting

Thursday, November 8, 2018 - 5:00pm - 5:30pm
Abdus Wahed (University of Pittsburgh)
Hypothesis testing to compare dynamic treatment regimes (DTR) from a sequential multiple assignment randomization trial (SMART) is generally based on inverse probability weighting or g-estimation. However, regression methods allowing for comparison of DTRs that flexibly adjust for baseline covariates using these methods are not as straight-forward due to the fact that one patient can belong to multiple DTRs. This poses a challenge for data analysts as it violates basic assumptions of regression modeling of unique group membership.
Thursday, September 14, 2017 - 2:45pm - 3:15pm
David Vock (University of Minnesota, Twin Cities)
Patients awaiting cadaveric organ transplantation face a difficult decision if offered a low-quality organ: accept the organ or remain on the waiting list and hope a better organ is offered in the future. A dynamic treatment regime (DTR) for transplantation is a rule that determines whether a patient should decline an offered organ. Existing methods can estimate the effect of DTRs on survival outcomes, but these were developed for applications where treatment is abundantly available.
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