I am looking at some data with a 5 factors and a response variable. The experiment was designed as a factorial experiment, with observations at different levels of each factor. One thing that I have notices, though, is that there is some variability in the readings for the factor levels.
For example, motor RPM is a variable, and readings were supposed to be recorded at 800 RPM, 1000 RPM and 1200 RPM. The experimenters were able to set the RPM at these levels for the experiment. There is an RPM monitor that keeps track of the RPM during the experiment, and is recorded along with the data. However, looking at the data, we see that there are slight variations. For example, when set at 800 RPM, we have readings that range between around 790 and 810 RPM. This occurs for all five of our factor variables. The RPM variability is negligible, but some factors are varying more than 15 percent of the desired factor level. This may be due to some error in the readings of the monitoring equipment.
My question is, can I ignore the variability in the factor levels and assume that we read the observations at those factor levels, or can I take into account the factor level variability when doing the analysis?