Complex experimental designs present unique challenges in the analysis of microRNA (miRNA) Cycle to Threshold (Ct) values. In this manuscript, we discuss various statistical techniques and their application in an analysis performed at the JG Brown Cancer Center. We consider data quality evaluation, data normalization, and statistical hypothesis procedures all in context of the example. The experiment utilized as the motivating example involved repeated sampling over time. The intra-subject correlation created by the repeated sampling should be incorporated into the analysis resulting in additional significant miRNAs. The statistical techniques leveraged to analyze miRNA Ct values resulting from qPCR should incorporate key features of the experimental design. It discusses potential issues with the commonly used methodologies when the experiment collects multiple samples from the same individuals over time.