What you want to do makes no sense. Would you care to explain why you think you want to do it?
-- Bert On Tue, Apr 23, 2013 at 1:41 PM, li li <hannah....@gmail.com> wrote: > Dear all, > I want to fit a random effect model with only one random factor. I do not > want to > include the intercept term either. > The model I using now is > > lmer(values ~ (1|lot), data=tmp) > > The results are as below. How do I take out the intercept term? Or > if this is not possible for the lmer function, is it possible using lme > function in the "nlme" package? > Thank you very much in advance. > Hanna > > > Linear mixed model fit by REML > Formula: values ~ (1 | lot) > Data: resamp > AIC BIC logLik deviance REMLdev > -14.21 -9.459 10.1 -23.88 -20.21 > Random effects: > Groups Name Variance Std.Dev. > lot (Intercept) 0.036077 0.18994 > Residual 0.017278 0.13144 > Number of obs: 36, groups: lot, 10 > Fixed effects: > Estimate Std. Error t value > (Intercept) 99.78693 0.06421 1554 > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ R-help@r-project.org 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.
