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.hlx at 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]]
>
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> 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