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Dear all, I am planning to use nlme library for analysis of experiments in semiconductor industry. Currently I am using "lm" but plan to move to "lme" to handle within wafer / wafer-to-wafer and lot-to-lot variation correctly. So far everything is working well, but I have a fundamentel question: NLME offers "maximum likelihood" and "restricted maximum likelihood" for parameter estimation. ML has the advantage, that likelihood ratios can be computed even with changes in model structure. In addition, ML works with the stepAIC function from MASS-library whic...