search for: glmpower

I've been searching for an answer to this for a while but no joy. I have a simple 2-way ANOVA with an interaction. I'd like to determine the power of this test for each factor (factor A, factor B, and the A*B interaction). How can I do this in R? I used to do this with "proc Glmpower" in SAS, but I can find no analogue in R. [[alternative HTML version deleted]]

...n = 20 between.var = 10.5 within.var = 9 sig.level = 0.05 power = 1 NOTE: n is number in each group I've already done the calculation in SAS with the following code: data Dep; Input cue $ mean weight; datalines; A 17.5 1 B 19 1 C 25 1 D 20.5 1 ; proc glmpower; class cue; model mean = cue; weight weight; power stddev = 9 alpha = 0.05 ntotal= 80 power = .; run; This produces a power of 0.616 which is the answer I was supposed to get. Any idea what I need to change? Will [[alternative HTML version deleted]]

...sus 0.680. So is there a straightforward way to compute the power of an unbalanced ANOVA? If there isn't, does anyone have any idea what is wrong with my code? The SAS I am comparing it to is: Data Dep; Input cue $ mean uneven_weight; datalines; A 17.5 1 B 19 1 C 25 5 D 20.5 1 ; proc glmpower; class cue; model mean = cue; weight uneven_weight; power stddev = 9 alpha = 0.05 ntotal= 80 power = .; run; Any help would be much appreciated. Will [[alternative HTML version deleted]]

For various reasons, I spent part of my time today looking at sample size and power calculation tools (don't ask, don't tell...). This seems to be one area that R is incredibly weak in (well, nearly all stat packages, except perhaps specialized tools and SAS); sure, there are a number of functions in various packages: base, statmod, Hmisc Have I missed something? (I