[R-sig-ME] lme4 sanple size analysis / power analysis by simulation ...

Kevin E. Thorpe kevin.thorpe at utoronto.ca
Tue Oct 22 19:51:29 CEST 2013


On 10/22/2013 01:45 PM, David Winsemius wrote:
>
> On Oct 22, 2013, at 6:35 AM, Lenth, Russell V wrote:
>
>> The reviewers were NOT correct in questioning whether you had
>> sufficient power. Power is the probability of rejecting a null
>> hypothesis. You have the data, you did your analysis, so you know
>> which hypotheses were rejected (retrospectively, the power of those
>> is 1) and those you did not (retrospective power of 0). There is no
>> more information about power to be gleaned with respect to those
>> data and analyses. You can use power calculations to decide sample
>> size for a future study only.
>
> Don't we need to know what conclusions were being questioned when we
> say this? I don't disagree about the vacuity of doing post-hoc power
> analyses, especially when the study of a rare condition will
> effectively place a hard limit on sample size. However, if
> conclusions were being submitted about "no difference" for the
> features that were "not significant", isn't it possible that
> questions about power would have validity?

I guess the obvious response to this is "power for what?"  In such 
situations, I think a careful consideration of confidence intervals in 
the context of clinical significance is far more helpful.

Kevin

>
>>
>> Russ
>>
>> -- Russell V. Lenth  -  Professor Emeritus Department of Statistics
>> and Actuarial Science The University of Iowa  -  Iowa City, IA
>> 52242  USA Dept office (319)335-0712  -  FAX (319)335-3017
>> russell-lenth at uiowa.edu  -  http://www.stat.uiowa.edu/~rlenth/
>>
>> ... The paper was accepted with revisions which is where we are
>> now. The reviewers correctly questioned to what extent we had
>> sufficient power to come to the conclusions we did. I do not want
>> to perform a post-hoc power analysis because from what I have read
>> and seen on R discussions it is discouraged. ...
>>


-- 
Kevin E. Thorpe
Head of Biostatistics,  Applied Health Research Centre (AHRC)
Li Ka Shing Knowledge Institute of St. Michael's
Assistant Professor, Dalla Lana School of Public Health
University of Toronto
email: kevin.thorpe at utoronto.ca  Tel: 416.864.5776  Fax: 416.864.3016



More information about the R-sig-mixed-models mailing list