Good afternoon,
I ran two different experiments using a CCD and received confusing results for both. Each experiment represents 2 different materials, they are not replicates of each other.
Each experiment was a face-centered CCD with 2 blocks, each block being a replicate. Each block does have variation within the samples. I assume the block is not significant in the model because there’s a good amount of within variance that makes the between variance negligible (I’m working with bacteria and the inoculum varies no matter what I do – it follows the poisson distribution). The outcome is presence (1)/ absence (0). The goal is 100% presence.
When I run fit nominal logistic and keep all variables in the model, the p-value for Whole Model Test for both experiments is <0.05 and the Lack of Fit is >0.05. However, when I start removing insignificant effects the lack of fit becomes <0.05.
I can’t figure out the best way to move forward. Should I do a third replicate for each experiment? Augment it with axial points (make it rotatable)? Leave in all variables? Use the profiler “as is” after removing variables (with lack of fit <0.05) and see if it works?
Thank you in advance for the help!