It seems I have things set up correctly. I suspect that the arguments
sshc(100,10) are the isuue. It seems that the 100,10 is not necessary since
the code itself specifies the arguments. It runs and produces a power curve if
I simply type sshc() but it also seems to try to keep running somethng as I
have to click stop to get back to a prompt in the console.
Why specify 100,10? There are 9 arguments, 3 which are required and the rest
optional. Shouldn't I have to specify the 3 required arguments, nc, d and
method at a minimum? It would look like sshc(nc=500, d=.5, method=3), right?
I;m still not sure, however, why that would be necessary since it's hard coded.
________________________________
From: Barry Rowlingson <b.rowling...@lancaster.ac.uk>
Cc: "r-help@r-project.org" <r-help@r-project.org>
Sent: Wednesday, October 5, 2011 9:27 AM
Subject: Re: [R] SPlus to R
ote:
> Hope I did this right. I repeated what I'd done before:
>
> 1) Opened script
> 2) Selected run all (this produced my inital post
>
> Then as suggested I:
>
> 3) Typed ls()
> 4) Saw that the function was present and issued sshc(100,10)
>
> Here's what I got:
>
>> ls()
> [1] "c.searchd" "convex" "Epower" "nef" "nef2" "power1.f"
> [7] "ss.rand" "sshc" "vertex"
>> sshc(100,10)
> Error in return(ne = ne, Ep = Ep1) :
> multi-argument returns are not permitted
> So it looks like I need to change the return(ne = ne, Ep = Ep1) to two
> separate lines, correct?
>
> On a brighter note, I did get a power curve as expected. One thing I don't
> understand is the meaning of the arguments in sshc(100,10).
There are some comments in the function code that tell you:
# rc number of response in historical control group
# nc sample size in historical control
# d target improvement = Pe - Pc
# method 1=method based on the randomized design
# 2=Makuch & Simon method (Makuch RW, Simon RM. Sample size
considerations
# for non-randomized comparative studies. J of Chron Dis
1980; 3:175-181.
# 3=uniform power method
######## optional Input:
- and so on.
Beyond that, I'll have to defer to people who know what this is
actually trying to compute...
Also, its highly possible that this code has already been ported to R
- lots of things have. If you know what its meant to compute then a
quick search might get you running quicker.
Barry
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