I am trying to compare the efficacy of two devices. Three different operators tested each device for a parameter of interest (the same 3 operators for each device) and yielded two data sets for each device. My first thought was to perform a simple two sample t-test on the data sets; however, it occurred to me that this would be ignoring which data was collected by which operator. It is suspected that the devices perform differently depending on who is using them and I would thus like to be able to mitigate this additional source of variability by blocking the data based on which operator collected it. After doing some research it appears that ANOVA can take into account such blocking. My two questions are:
Am I correct that ANOVA is the appropriate test to use in this case?
Is ANOVA always going to be more powerful than a two-sample t-test in this case or would I be just as well off simply performing the t-test?
Just to be extra clear, my goal is not to assess the degree of variability introduced my using multiple operators but simply to remove it as a confounding variable and only compare the efficacy of one device to the other.
