Dear all, 

 

 

In the sizepower package, when I compute the power for a paired design,
(block of size 2), with the following parameters: 

 

Ero=5 

Go=20000

absMu1=1.0

sigmad=0.6

n=8, being *n* the sample size for each group.- 

 

I obtain: 

 

> power.matched(5,20000,1.0,.6,8)

$power

[1] 0.853551

 

 

If I compute the power for the same design, but using a function especially
writen for a block design (I have a block of size 2), I use: 

 

Ero=5 

Go=20000

numTrt=2, being this the total number of treatment conditions

absMu1=1.0

sigmad=0.6

n=8, being n the sample size for each group.- 

 

I obtain: 

 

> power.multi(5,20000,2,1,.6,8)

$power

[1] 0.3711056

 

which is a different result than the power.mathed gives, however if I use: 

 

> power.multi(5,20000,2,1,.6,16)

$power

[1] 0.853551

 

both functions render now the same result. 

 

I am bit puzzled, because the documentation of the package says that *n* is
the sample size for each group, and in this example is 8 not 16 !! 

Moreover, an additional documentation of the package, says for the
power.multi function, that *n* is the number of the blocks. 

 

In addition, if I consider a complete randomized design, with the same
parameters as before:

 

Ero=5 

Go=20000

absMu1=1.0

sigmad=0.6

n=8, being *n* the sample size for each group.-

 

 

> power.randomized(5,20000,1,0.6,8)

$power

[1] 0.853551

 

I obtain the same power than for a paired design, and this should be
smaller, shouldn’t it? 

 

Could anyone explain this to me? 

 

Thanks a lot. 

 

 

My sessionInfo is: 

 

R version 2.4.0 (2006-10-03) 

i386-pc-mingw32

 

sizepower       

   "1.4.0"

 

 

Pedro 

 

 

 

 

 

 

 

 

 


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