[R] how to determine power in my analysis?

[Bert Gunter]

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.glover at 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: djmuser at gmail.com
>> To: kristi.glover at hotmail.com
>> CC: gunter.berton at gene.com; r-help at 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.glover at 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.berton at gene.com
>> >> To: kristi.glover at hotmail.com
>> >> CC: r-help at 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.glover at 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 at 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 at 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.