title: Comment on "Dynamic treatment regimes: technical challenges and applications"
abstract: 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.
authors.affiliation: Department of Statistics, University of Haifa, Mount Carmel, Haifa 31905, Israel.
authors.forename: Yair
authors.initials: Y
authors.lastname: Goldberg
authors.affiliation: Department of Statistics, North Carolina State University, Raleigh, NC 27695, U.S.A.
authors.forename: Rui
authors.initials: R
authors.lastname: Song
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, U.S.A.
authors.forename: Donglin
authors.initials: D
authors.lastname: Zeng
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, U.S.A.
authors.forename: Michael R
authors.initials: MR
authors.lastname: Kosorok