Hi Kristi: I think this paper elucidates the problem Bert mentioned. A thorough and careful reading of the last two sections should clarify what post-hoc power is and is not.
http://www.stat.uiowa.edu/files/stat/techrep/tr378.pdf Dennis On Sat, Nov 8, 2014 at 11:25 AM, Kristi Glover <kristi.glo...@hotmail.com> wrote: > Hi Bert, Thanks for the message. So far I know we can test whether my sample > size in my analysis is enough or not. It is also post hoc property. For > example, we can calculate standard deviations, error variance etc in the > data sets, and then we can use them to determine whether the sample size was > enough or not with certain level of alpha and power. we can do it is some of > the statistical programs, but I was not aware in R. thanks KG > >> Date: Sat, 8 Nov 2014 10:55:56 -0800 >> Subject: Re: [R] how to determine power in my analysis? >> From: gunter.ber...@gene.com >> To: kristi.glo...@hotmail.com >> CC: r-h...@stat.math.ethz.ch >> >> Kristi: >> >> Power is a prespecified property of the design, not a post hoc >> property of the analysis (SAS procedures notwithstanding). So you're a >> day late and a dollar short. >> >> I suggest you consult with a local statistician about such matters, as >> you appear to be out of your depth. >> >> Cheers, >> Bert >> >> Bert Gunter >> Genentech Nonclinical Biostatistics >> (650) 467-7374 >> >> "Data is not information. Information is not knowledge. And knowledge >> is certainly not wisdom." >> Clifford Stoll >> >> >> >> >> On Sat, Nov 8, 2014 at 3:49 AM, Kristi Glover <kristi.glo...@hotmail.com> >> wrote: >> > Hi R Users, >> > I was trying to determine whether I have enough samples and power in my >> > analysis. Would you mind to provide some hints?. I found a several >> > packages for power analysis but did not find any example data. I have two >> > sites and each site has 4 groups. I wanted to test whether there was an >> > effect of restoration activities and sites on the observed value. I used a >> > two way factorial ANOVA and now I wanted to test the power of the analysis >> > (whether the sample sizes are enough for the analysis? what are the alpha >> > and power in the analysis using this data set? if it is not enough, how >> > much samples should be collected for alpha 0.05 and power=0.8 and 0.9 for >> > the analysis (two way factorial analysis). >> > The example data:data<-structure(list(observedValue = c(0.08, 0.53, 0.14, >> > 0.66, 0.37, 0.88, 0.84, 0.46, 0.3, 0.61, 0.75, 0.82, 0.67, 0.37, 0.95, >> > 0.73, 0.74, 0.69, 0.06, 0.97, 0.97, 0.07, 0.75, 0.68, 0.53, 0.72, 0.34, >> > 0.12, 0.49, 0.77, 0.45, 0.07, 0.97, 0.34, 0.68, 0.48, 0.65, 0.7, 0.57, >> > 0.66, 0.4, 0.29, 0.88, 0.36, 0.68, 0.32, 0.8, 0, 0.11, 0.48, 0.85, 0.94, >> > 0.12, 0.12, 0, 0.89, 0.66, 0.2, 0.57, 0.09, 0.27, 0.81, 0.53, 0.09, 0.5, >> > 0.41, 0.89, 0.47, 0.39, 0.85, 0.71, 0.89, 0.01, 0.71, 0.42, 0.72, 0.62, >> > 0.3, 0.56, 0.99, 0.97, 0.03, 0.09, 0.27, 0.27, 0.94, 0.23, 0.97, 0.81, >> > 0.95), condition = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, >> > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, >> > 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, >> > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, >> > 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, >> > 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("goo! d! > ", "! >> > medium", "poor", "verygood"), class = "factor"), areas = structure(c(1L, >> > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >> > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >> > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, >> > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, >> > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), >> > .Label = c("Restored", "unrestored"), class = "factor")), .Names = >> > c("observedValue", "condition", "areas"), class = "data.frame", row.names >> > = c(NA, -90L)) >> > test= aov(observedValue~condition*areas,data=data)summary(test) >> > power of the analysis? >> > thanks for your help. >> > Sincerely, KG >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help@r-project.org mailing list >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html >> > and provide commented, minimal, self-contained, reproducible code. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
