It seems although your are trying to do a retrospective power calculation -
not something to be encouraged. 

I don't think that power.t.test was designed to work on observed data in the
way you seem to want to use it. You could use power.t.test to do a
prospective calculation where you know the difference (delta) and the sd...

Saghir

-----Original Message-----
From: r-help-bounces@stat.math.ethz.ch
[mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Jim BRINDLE
Sent: Thursday, May 19, 2005 16:39
To: r-help@stat.math.ethz.ch
Subject: [R] Power w/ unequal sample sizes


Hello,

I am hoping someone could shed some light on power calculations for me.  I 
have two small data sets of unequal sample size after NA removal (m = 5, f =

7).

m <- c(2.0863, 2.1340, 2.1008, 1.9565, 2.0413, NA, NA)
f <- c(1.8938, 1.9709, 1.8613, 2.0836, 1.9485, 2.0630, 1.9143)

In a R help message/reply from Sep 30, 2001, it was noted that the 
"power.t.test" function assumes equal group sizes and that the groups have 
the same theoretical standard deviation.  In "analyzing" this data, I ran a 
Welch Two Sample t-test and a Wilcoxon Rank Sum test on the data sets and 
both tests reveal a slight statistical difference for alpha = 0.05 (Welch 
Two Sample t-test p-value = 0.045 and Wilcoxon Rank Sum test p-value = 
0.048).

I suspect that the "power" of these tests will be quite low but I am trying 
to quantify it.  Based on the insight in the R help message from 2001, I am 
not sure how to go about this with R.  Is this feasible with R or is there 
another approach I should be considering altogether?

Any insight would be most appreciated.  Thanks a million....

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