Hello all,

I would like to plan and analyse a study with "k" treatments (one of which
is a "control"), with some binary outcome, in order to find the "best"
treatment (e.g: the one with a high number of "successes").
If this was done with a fixed sample size, the analysis is well known.
 However, I would rather be able to "drop" treatment(s), if at any (or some
specific) point in the analysis, I find it (or them) inferior to the
control.

*What correction/analysis might I use in order to find the "best
treatment", while dropping "bad treatments" during the experiment?*

After searching through google scholar, the most relevant article I found
was "Drop-the-losers design: Binomial case" by Michael W. Sill , Allan R.
Sampson -
yet I was not able to find an implementation for their ideas.

Thanks up front for any lead/idea on this topic.


(p.s: this question was also cross-posted to
http://stats.stackexchange.com/questions/22355/suggestion-for-drop-the-loser-design-and-analysis-in-r
)

With regards,
Tal

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