Select the maximum tolerated dose (MTD) when the singleagent trial is completed
1  select.mtd(target, npts, ntox, cutoff.eli=0.95, extrasafe=FALSE, offset=0.05, print=TRUE)

target 
the target toxicity rate 
npts 
a vector containing the number of patients treated at each dose level 
ntox 
a vector containing the number of patients who experienced doselimiting toxicity at each dose level 
cutoff.eli 
the cutoff to eliminate overly toxic doses for safety. We recommend
the default value of ( 
extrasafe 
set 
offset 
a small positive number (between 0 and 0.5) to control how strict the
stopping rule is when 
print 
to print out the dose selection result 
select.mtd()
selects the MTD based on isotonic estimates of toxicity
probabilities. select.mtd
selects as the MTD dose j*, for which the
isotonic estimate of the toxicity rate is closest to the target. If there
are ties, we select from the ties the highest dose level when the estimate
of the toxicity rate is smaller than the target, or the lowest dose level
when the estimate of the toxicity rate is greater than the target. The
isotonic estimates are obtained by the pooledadjacentviolators algorithm
(PAVA) (Barlow, 1972).
select.mtd()
returns the MTD based on the trial data.
The MTD selection and dose escalation/deescalation rule are two independent components of the trial design. When appropriate, another dose selection procedure (e.g., based on a fitted logistic model) can be used to select the MTD after the completion of the trial using the BOIN design.
Suyu Liu and Ying Yuan
Liu S. and Yuan, Y. (2015). Bayesian Optimal Interval Designs for Phase I Clinical Trials, Journal of the Royal Statistical Society: Series C, 64, 507523.
Tutorial: http://odin.mdacc.tmc.edu/~yyuan/Software/BOIN/BOIN2.4_tutorial.pdf
Paper: http://odin.mdacc.tmc.edu/~yyuan/Software/BOIN/paper.pdf
1 2 3  n<c(3, 3, 15, 9, 0)
y<c(0, 0, 4, 4, 0)
select.mtd(target=0.3, npts=n, ntox=y)

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