[R] Code modification for post-hoc power

[CHATTON Anne]

Dear Michael,

Thanks a lot for your suggestion. This is what I am trying to do with R (longpower and gee packages). But I am getting stuck with a confusing error message sent earlier I don't understand.

Best,

Anne

-----Message d'origine-----
De : Michael Dewey [mailto:lists using dewey.myzen.co.uk] 
Envoyé : lundi, 26 août 2019 18:29
À : Marc Schwartz <marc_schwartz using me.com>; CHATTON Anne <Anne.Chatton using hcuge.ch>
Cc : R-help <r-help using r-project.org>
Objet : Re: [R] Code modification for post-hoc power

Dear Anne

In addition to Marc's comments if you are forced to do this then, assuming your package computes sample size from power then just feed it a range of powers and find the one for which it calculates the sample size you had. There is a more elegant way to do this using uniroot but brute force should work.

Michael

On 26/08/2019 13:42, Marc Schwartz via R-help wrote:
> 
>> On Aug 26, 2019, at 6:24 AM, CHATTON Anne via R-help <r-help using r-project.org> wrote:
>>
>> Hello everybody,
>>
>> I am trying to accommodate the R codes provided by Donohue for sample size calculation in the package "longpower" with lmmpower function to estimate the post-hoc power (asked by a reviewer) of a binary GEE model with a three-way interaction (time x condition x continuous predictor) given a fixed sample size. In other words instead of the sample size I would like to estimate the power of my study.
>>
>> Could anyone please help me to modify these codes as to obtain the power I'm looking for.
>>
>> I would really appreciate receiving any feedback on this subject.
>>
>> Yours sincerely,
>>
>> Anne
> 
> 
> Hi,
> 
> Three comments:
> 
> 1. Don't calculate post hoc power. Do a Google search and you will find a plethora of papers and discussions on why not, including these:
> 
>    The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis
>    The American Statistician, February 2001, Vol. 55, No. 1
>    https://www.vims.edu/people/hoenig_jm/pubs/hoenig2.pdf
> 
>    Post Hoc Power: Tables and Commentary
>    https://stat.uiowa.edu/sites/stat.uiowa.edu/files/techrep/tr378.pdf
> 
>    Observed power, and what to do if your editor asks for post-hoc power analyses
>    
> http://daniellakens.blogspot.com/2014/12/observed-power-and-what-to-do
> -if-your.html
> 
>    Retraction Watch:
>    Statisticians clamor for retraction of paper by Harvard researchers they say uses a “nonsense statistic”
>    
> https://retractionwatch.com/2019/06/19/statisticians-clamor-for-retrac
> tion-of-paper-by-harvard-researchers-they-say-uses-a-nonsense-statisti
> c/
> 
>    PubPeer Comments on the paper cited in the above RW post:
>    https://pubpeer.com/publications/4399282A80691D9421B497E8316CF6
> 
>    A discussion on Frank's Data Methods forum also related to the same paper cited above:
>    "Observed Power" and other "Power" Issues
>    
> https://discourse.datamethods.org/t/observed-power-and-other-power-iss
> ues/731/30
> 
> 
> 2. If you are still compelled (voluntarily or involuntarily), you may want to review the vignette for the longpower package which may have some insights, and/or contact the package maintainer for additional guidance on how to structure the code. See the vignette here:
> 
>    
> https://cran.r-project.org/web/packages/longpower/vignettes/longpower.
> pdf
> 
> 
> 3. Don't calculate post hoc power.
> 
> 
> Regards,
> 
> Marc Schwartz
> 
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--
Michael
http://www.dewey.myzen.co.uk/home.html