Hello, Its my first time to deal with Longitudinal analysis in Limma and I would like to make sure that my design reflects my research question. Research question: which gene-expressions are significantly differentially expressed over time with the change of FEV1 (continuous variable) overtime. I have 2 gene expression, FEV1, and other covariants readings for 2 timepoints.

```
RID<-factor(rownames(combined_pheno)) #reading ID is different for each reading
ID<-factor(combined_pheno$SubjectID) # each subject has 1 ID and 2 RID
design<- model.matrix(~FEV1+Time+FEV1:Time+ Age+Gender+Race)
fit<-voomLmFit(exp , design, block=ID, plot=TRUE)
fit<- eBayes (fit)
result<- topTable(fit,coef="FEV1:Time",n=Inf,adjust="BH",p.value = 0.05 , sort.by = "logFC")
sessionInfo( )
```

My question would be is it right to assume that "ID" is counted as random effect by adding (block=ID) Thank you

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