This is discussion is now off topic here. Either post elsewhere, e.g stats.stackexchange.com, or consult your local statistician for help, as I previously suggested.
-- 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 2:56 PM, Kristi Glover <kristi.glo...@hotmail.com> wrote: > Dear Dennis, > I really appreciated for your and Bert's help. I read the paper and it seems > that once the study is completed, power calculations do not inform us in any > way as to the conclusions of the present study. But I am really now confused > whether we can't improve the research design for future or next year > monitoring based on the present results. I would really be grateful for your > suggestions and insights. Can't we take reference from the present study for > improving future sampling? > Thanks > KG > >> Date: Sat, 8 Nov 2014 13:36:35 -0800 >> Subject: Re: [R] how to determine power in my analysis? >> From: djmu...@gmail.com >> To: kristi.glo...@hotmail.com >> CC: gunter.ber...@gene.com; r-h...@stat.math.ethz.ch >> >> 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("good! >> > ", "! >> >> > 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.
