IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Adaptive Minimax-Regret Treatment Choice, With Application To Drug Approval

Listed author(s):
  • Charles F. Manski

Suppose that there are two treatments for a condition. One is the status quo, whose properties are known from experience and the other is an innovation, whose properties are not known initially. A new cohort of persons presents itself each period and a planner must choose how to treat this cohort. When facing situations of this kind, it has become common to commission randomized trials of limited duration to learn about the innovation. Rather than wait for the outcomes of interest to unfold over time, surrogate outcomes that can be observed early on are used to judge the success of the innovation. A close approximation to this process is institutionalized in the drug approval protocol of the U. S. Food and Drug Administration. This paper brings welfare-economic and decision-theoretic thinking to bear on the problem of treatment choice, with application to drug approval. I introduce the adaptive minimax-regret (AMR) rule, which applies to each cohort the minimax-regret criterion using the knowledge of treatment response available at the time of treatment. The result is a fractional treatment allocation whenever the available knowledge does not suffice to determine which treatment is better. The rule is adaptive because, as knowledge of treatment response accumulates, successive cohorts are allocated differently across the two treatments. I use the AMR idea to suggest an adaptive drug approval process that permits partial marketing of new drugs while scientifically appropriate long-term clinical trials are underway. The stronger the evidence on health outcomes of interest, the more treatment would be permitted, with a definitive approval decision eventually made when sufficient evidence has accumulated.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: no

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 13312.

in new window

Date of creation: Aug 2007
Handle: RePEc:nbr:nberwo:13312
Note: HC HE PE
Contact details of provider: Postal:
National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.

Phone: 617-868-3900
Web page:

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

in new window

  1. Stoye, Jörg, 2009. "Minimax regret treatment choice with finite samples," Journal of Econometrics, Elsevier, vol. 151(1), pages 70-81, July.
  2. Manski, Charles F., 2007. "Minimax-regret treatment choice with missing outcome data," Journal of Econometrics, Elsevier, vol. 139(1), pages 105-115, July.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:13312. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.