Comment on “Dynamic treatment regimes: Technical challenges and applications”

Yair Goldberg, Rui Song, Donglin Zeng, Michael R. Kosorok

Research output: Contribution to journalArticlepeer-review


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. Received May 2014.

Original languageEnglish
Pages (from-to)1290-1300
Number of pages11
JournalElectronic Journal of Statistics
StatePublished - 2014

Bibliographical note

Publisher Copyright:
© 2014, Institute of Mathematical Statistics. All rights received.

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


Dive into the research topics of 'Comment on “Dynamic treatment regimes: Technical challenges and applications”'. Together they form a unique fingerprint.

Cite this