I need to calculate the sample size for a study of biomarkers which indicate the progress of a disease. The samples will be collected at baseline, 12, 24,36 and 48 months and will be tested against 15 CSF biomarkers. A pilot study has been done with 15 patients which I would like to use as prior information. I believe that the biomarkers are independent but there also could be some correlation. The study question is to see if the continuous measurements of each biomarker changes over time. The biomarkers values are not normally distributed. I have tried Gpower software using non parametric Anova for repeated measure. My first question is whether I need to calculate the sample size for each biomarker individually using Bonferroni correction 0.05/15 and then choose the largest sample size, or to calculate the sample size for all biomarkers together. Another question, for the gpower I would need, no sphericity correction, epsilon, correlation between time points and eta square, I tried to calculate them using proc glm, as proc glm data=data; class timepoint; model biom= ... repeated timepoint/ Printe; run; But didn't get what I want. Do you know how can I obtain those values and shall I assume data for each biomarker separately?
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