For optimal response surface design (one-factor), if my independent factor has several levels with repeated measures (assuming outliers are removed), is it correct to input all these individual result points, or do I take the average result of each level and input them?
Yes, by seeing if the surface bisects the points and fits them within normal variation (does not exhibit a significant lack of fit). To see what I mean, open the tutorial data Chemical Conversion (Analyzed), go to the Model Graphs, 3D Surface and click through the Jump to run points. This is an example of RSM done right. : ) You can access the Stat-Ease tutorials at www.statease.com/docs/latest/tutorials
For optimal response surface design (one-factor), if my independent factor has several levels with repeated measures (assuming outliers are removed), is it correct to input all these individual result points, or do I take the average result of each level and input them?
Always average repeated measures. Do not enter each one as an individual run (design point).
Is there any way to know if rsm is done right by looking at 3D graph
Yes, by seeing if the surface bisects the points and fits them within normal variation (does not exhibit a significant lack of fit). To see what I mean, open the tutorial data Chemical Conversion (Analyzed), go to the Model Graphs, 3D Surface and click through the Jump to run points. This is an example of RSM done right. : )
You can access the Stat-Ease tutorials at www.statease.com/docs/latest/tutorials