*! version 1.0 25 May 2018

Title

cedesign -- A command to find the optimal flexible two stage single-arm binary outcome design using the discrete conditional error function.

Syntax

cedesign
[,
options]

Main
p1(#) specifies the alternative probability that the study is powered for. Default value is 0.3.

p0(#) specifies the null probability that is used in the null hypothesis. Default value is 0.1.

alpha(#) specifies the significance level. Default value is 0.05.

beta(#) specifies the type II eror level. Default value is 0.1.

n1min(#) specifies the minimum first stage sample size. Default value is 2.

n1max(#) specifies the maximum first stage sample size. Default value is 22.

n2min(#) specifies the minimum second stage sample size. Default value is 2.

n1n2max(#) Default value is 50.

Description

This command creates a two-stage fully flexible design with a binary outcome variable, often response or not,
that uses a conditional error function. The design usually is interested in rejecting the null hypothesis
that response is H0: p=p0. The methods are published by S. Englert and M. Keiser (2012)
Improving the flexibility and efficiency of phase 2 designs for oncology trials, Biometrics.

A discrete conditional error function, D(i) is defined for the number of responders, i, in the first phase
of the trial. If the second stage p-value is < D(i) then the null hypothesis is rejected. The function D() must
be non-decreasing with i but this command allows no other restrictions on what D() can take. However,
there is no point picking values other than the discrete set of second stage p-values.

However, there are a huge number of possible first stage and second stage sample sizes but this command will
search over a range of values and find the optimal one. It can take a huge amount of time if you pick large
sample sizes but the search
uses a branch and bound algorithm, so is efficient. Currently the optimal one is one that has the smallest expected
sample size at p0.

Options

Main

p1(#) specifies the alternative probability that the study is powered for. Default value is 0.3

p0(#) specifies the null probability that is used in the null hypothesis. Default value is 0.1

alpha(#) specifies the significance level. Default value is 0.05

beta(#) specifies the type II eror level. Default value is 0.1

n1min(#) specifies the minimum first stage sample size. Default value is 2

n1max(#) specifies the maximum first stage sample size. Default value is 22

n2min(#) specifies the minimum second stage sample size. Default value is 2

n1n2max(#) Default value is 50

Examples

Assuming that p0=0.1, p1=0.5,we can run the command

cedesign, p0(0.1) p1(0.5) n1min(5) n1n2max(30)

Author

Dr Adrian Mander, MRC Biostatistics Unit, University of Cambridge.

Email adrian.mander@mrc-bsu.cam.ac.uk

See Also

Related commands:

simon2stage (if installed) install by clicking ssc install simon2stage

crm (if installed) install by clicking ssc install crm