I would like to set up an experiment with different sets of covariates:
- Set 1: Batch with Supplier nd Moisture as covariates
- Set 2: Laboratory analytical run, with Technician as covariate
The goal is to determine the effect of different factors in the manufacturing process (speed, force...), and assign the Batches/Suppliers/Moisture to the different processing runs.
However, since lab variation will affect the measure of interest, I also want the different experimental units made in production to be analysed by the lab such that the estimates of the factors of interest are not skewed by lab variation. For example, I don't want all the high force samples to be analysed on the same day/analytical run in the lab, or on different runs but by the same technician.
I can only get the custom designer to use 1 set of covariates, from 1 table. Is there a way to use two independent sets of covariates?
Maybe I didn't describe what I am trying to do very well.
- I have 3 covariates in Set 1 (raw material covariates). Batch #, supplier and moisture are related (and are all be different columns in the same data table).
- I have 2 covariates in Set 2 (analytical covariates), the lab run and Technician (different columns in 2nd data table).
- I have independent process variables (speed, force...)
Obviously Set 1 and Set 2 are independent of each other. And the process variables are independent of each other and independent of the different Sets.
Is there a way to use both Sets in the design? I know how to get the custom designer to include the independent process variables and either 1)Batch #/supplier/moisture OR 2)lab run/Technician in the design, but no both.