I have executed a study using a RSM methodology with 5 input factors, Custom design: D-Optimal, 28 runs and we realized during the interpretation of results that it would have been great to have included a 6th factor. Is it possible to "augment" my design at this stage and how can I design the extra runs? If you have had similar experience it would be great to hear from you. Thanks
Did you measure the level of the 6th factor during the initial 28 runs? If so, you might try including it in the model before augmenting. Add the appropriate column properties first.
Was the 6th held constant during the initial 28 runs? Is the level known? You still need to create this data column before augmenting the design. Afterwards, select DOE > Augment Design and proceed as usual. You might need to adjust the factor range and will certainly need to modify the model.
as Mark stated it is important if you have prior information of this parameter from the previous runs. If you have measured this parameter as additional variable, you can see if the model will tell you already something about its impact. If it was constant, this is not much but still some information.
If you have not measured it, nor information about what level it has during the 28 previous runs, you need to do as many runs as needed to estimate the main effect, 2-factor interaction effects of this 6th parameter with the previous five each, and the quadratic effect, to get a full understanding of its influence. (Of course having few more runs allows to estimate the error as always).
In case you know upfront specific interactions or quadratic effects cannot happen, you might want to adjust the model and reduce therefore the required number of runs.
Summarized, if you have already some information from the previous 28 runs you might need just a few more to fill the gaps, if you know nothing, you need to have at least one additional run for each additional model effect this parameter adds.
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