If these four items are not under control prior to experimenting, the best advice is to not experiment. If they can be ruled out as reasons for lack of confirmation, other areas can be investigated. These include something changing between the initial matrix experiment and the confirmation runs, lack of linearity (i.e., presence of a non-linear relationship), aliased terms, too few or too many terms in a model, etc.