|Title||Comment on "Dynamic treatment regimes: technical challenges and applications"|
|Publication Type||Journal Article|
|Year of Publication||2014|
|Authors||Goldberg, Yair, Rui Song, Donglin Zeng, and Michael R. Kosorok|
|Journal||Electron J Stat|
Inference for parameters associated with optimal dynamic treatment regimes is challenging as these estimators are nonregular when there are non-responders to treatments. In this discussion, we comment on three aspects of alleviating this nonregularity. We first discuss an alternative approach for smoothing the quality functions. We then discuss some further details on our existing work to identify non-responders through penalization. Third, we propose a clinically meaningful value assessment whose estimator does not suffer from nonregularity.
|Alternate Journal||Electron J Stat|
|Original Publication||Comment on "Dynamic treatment regimes: Technical challenges and applications"|
|PubMed Central ID||PMC4255986|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States|
Comment on "Dynamic treatment regimes: technical challenges and applications"