Daniel Lakeland <dlakelan <at> street-artists.org> writes: > > We have used the lmer package to fit various models for the various > experiments that she has done (random effects from multiple > measurements for each animal or each trial, and fixed effects from > developmental stage, and genotype etc). The results are fairly clear > cut to me, and I suggested that she publish the results as coefficient > estimates for the relevant contrasts, and their standard error > estimates. However, she has read the statistical guidelines for the > journal and they insist on p values. > > I personally think that p values, and sharp-null hypothesis tests are > misguided and should be banned from publications, but it doesn't much > matter what I think compared to what the editors want. > > Based on searching the archives, and finding this message: > > https://stat.ethz.ch/pipermail/r-help/2006-May/094765.html
..... >From what you describe, using the stable function lme in nlme by the same >author Douglas Bates would do the job better for you. Remember lmer is under development, which does not mean it's bad, but some nice things like weight are still missing. For lme, you have excellent documentation in the book by Pinheiro/Bates. Dieter ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
