BookmarkSubscribeRSS Feed
iuri_leite
Fluorite | Level 6

Dear Colleagues,

I am running a logistic model where the dependent variable is the logit of the probability of a patient being diagnosed with COVID-19. The dataset comprises 4,908 patients, of whom 1,729 tested positive for COVID-19. The dataset includes demographic and clinical information about the patients and information on the predominant variant (original, Gamma, Delta, and Omicron) at the time these patients sought care. In the final model, we identified three statistically significant interactions between the symptoms (runny nose, sore throat, and loss of smell) and the variant type.
I would like to know how to calculate these interactions' power.
Thank you in advance.
Best regards,
Iuri

3 REPLIES 3
StatDave
SAS Super FREQ
Define what exactly you mean by "power". I assume you don't mean the statistical power of the test of their parameters or that you mean their significance since that is given right in the parameter estimates table. If you mean their effects on the diagnosis probability, then you might mean their marginal effects which you could get from the Margins macro (http://support.sas.com/kb/63038).
iuri_leite
Fluorite | Level 6

Dear Dave,

I submitted a paper, and one of the reviewers raised a concern about the lack of a reported power calculation for the sample size: “No formal power calculation/sample size is reported. Given the number of predictors and interactions, it would be helpful to know if the study was adequately powered.”

I would like to discuss the best approach to calculate the power. In fact, we did not select a sample; we used data from all patients who sought assistance at a Primary Care Unit.

Therefore, I would like to find the best way to solve this problem.

Regard

 

StatDave
SAS Super FREQ

So you do apparently want statistical power. Power and sample size analysis can be done in PROC POWER for a planned study to be analyzed using a logistic model. See the example in the PROC POWER documentation. Note that PROC POWER is for prospective power analysis, not for a retrospective study that has already been designed and analyzed. Results from such a prospective analysis done in advance of you collecting data is apparently what your reviewer is asking for.

SAS Innovate 2025: Call for Content

Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 25. Read more here about why you should contribute and what is in it for you!

Submit your idea!

What is ANOVA?

ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 3 replies
  • 237 views
  • 0 likes
  • 2 in conversation