[R] gsDesign
Dongli Zhou
dongli.zhou at gmail.com
Wed Nov 16 00:43:17 CET 2011
Thank you so much for the help! It is really appreciated!
Dongli
On Nov 15, 2011, at 9:19 AM, Marc Schwartz <marc_schwartz at me.com> wrote:
> Hi Dongli,
>
> Sorry for the delay in following up.
>
> You might want to read the dsDesignManual.pdf document, which is available in the 'inst/doc' folder in the package source tarball on CRAN, or in the package 'doc' directory in your R installation. Use:
>
> system.file(package = "gsDesign")
>
> to get the package top directory for your installation. The above file will be in the 'doc' sub-directory from there. It has more extensive worked examples than the default package manual.
>
>
> Simple non-inferiority example from ?nBinomial, with 2:1 ratio:
>
> n.Fix <- nBinomial(p1 = .677, p2 = .677, delta0 = 0.07, ratio = 2)
>
>
>> n.Fix
> [1] 2056.671
>
> # Adjust that *up* to an integer multiple of 3
> n.Fix <- 2058
>
>
> # Change 'outtype' to 2 if you want to see per arm sample sizes
> # eg:
>> nBinomial(p1 = .677, p2 = .677, delta0 = 0.07, ratio = 2, outtype = 2)
> $n1
> [1] 685.5569
>
> $n2
> [1] 1371.114
>
>
>
>
> # Simple default GS design using the fixed study design sample size from above,
> # which is not yet adjusted for interim analyses
>
>> gsDesign(n.fix = n.Fix)
> Asymmetric two-sided group sequential design with
> 90 % power and 2.5 % Type I Error.
> Upper bound spending computations assume
> trial continues if lower bound is crossed.
>
> ----Lower bounds---- ----Upper bounds-----
> Analysis N Z Nominal p Spend+ Z Nominal p Spend++
> 1 734 -0.24 0.4057 0.0148 3.01 0.0013 0.0013
> 2 1468 0.94 0.8267 0.0289 2.55 0.0054 0.0049
> 3 2202 2.00 0.9772 0.0563 2.00 0.0228 0.0188
> Total 0.1000 0.0250
> + lower bound beta spending (under H1):
> Hwang-Shih-DeCani spending function with gamma = -2
> ++ alpha spending:
> Hwang-Shih-DeCani spending function with gamma = -4
>
> Boundary crossing probabilities and expected sample size
> assume any cross stops the trial
>
> Upper boundary (power or Type I Error)
> Analysis
> Theta 1 2 3 Total E{N}
> 0.0000 0.0013 0.0049 0.0171 0.0233 1286.0
> 0.0715 0.1412 0.4403 0.3185 0.9000 1628.4
>
> Lower boundary (futility or Type II Error)
> Analysis
> Theta 1 2 3 Total
> 0.0000 0.4057 0.4290 0.1420 0.9767
> 0.0715 0.0148 0.0289 0.0563 0.1000
>
>
> So rather than needing 2058 from the fixed design, you actually need 2202 (1468 in one arm and 734 in the other).
>
> I would urge you to read the manual I reference above and as Andy has noted in his reply, contact Keaven directly for further assistance with this package.
>
> HTH,
>
> Marc
>
> On Nov 14, 2011, at 5:13 PM, Dongli Zhou wrote:
>
>> Hi, Marc,
>>
>> Thank you very much for the reply. I'm using the gsDesign function to create an object of type gsDesign. But the inputs do not include the 'ratio' argument.
>>
>> Dongli
>>
>> On Nov 14, 2011, at 5:50 PM, Marc Schwartz <marc_schwartz at me.com> wrote:
>>
>>> On Nov 14, 2011, at 4:11 PM, Dongli Zhou wrote:
>>>
>>>> I'm trying to use gsDesign for a noninferiority trial with binary
>>>> endpoint. Did anyone know how to specify the trial with different sample
>>>> sizes for two treatment groups? Thanks in advance!
>>>
>>>
>>> Hi,
>>>
>>> Presuming that you are using the nBinomial() function, see the 'ratio' argument, which defines the desired sample size ratio between the two groups.
>>>
>>> See ?nBinomial and the examples there, which does include one using the 'ratio' argument.
>>>
>>> HTH,
>>>
>>> Marc Schwartz
>>>
>
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