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Posted 02-19-2020 03:04 PM
(2578 views)

Dear Experts,

I would appreciate your advice on calculating the power / sample size for an analysis of a ROC curve.

Assuming a prevalence of 6% positive screens on the gold standard clinical interview among eligible subjects, I am not really interested in detecting difference from chance (AUC=0.50) but rather superiority to a particular value (e.g, AUC=0.70) and have a basic power to detect that particular value (e.g. power= 0.70, or higher ). I expect the AUC for my test to be observed as high as ~0.90.

Much appreciated.

Ping

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I suspect this is not an easy problem, but it is an interesting question. I do not know the answer, but PROC POWER in SAS/STAT provides power /sample size calculations for the LR test, and it looks like the power depends on the distribution of the covariates and the correlation between the covariates, among other issues. It might also depend on your sampling scheme (e.g., are you oversampling a rare event?)

Again, I do not know the answer, but It seems like you have two options:

(1) search the literature to see if the answer is known and (if so) implement that option in SAS by using the DATA step or PROC IML

(2) simulation can estimate power and sample sizes, and might be simpler to implement. Again, you'll have to specify the distribution of the covariates and the parameters for the linear predictor. You'll have to estimate the parameters (difference of means, standard deviations, regression coefficients,...) from a previous study/analysis.

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