
You can unload nlme by using:
detach("package:nlme")


Jake

> Date: Mon, 25 Jun 2012 13:12:52 -0500
> From: emptican@gmail.com
> To: bates@stat.wisc.edu
> CC: r-sig-mixed-models@r-project.org
> Subject: Re: [R-sig-ME] sas to R
> 
> I restarted R and tried to fit the model.  However, I got the same
> message...  So, I checked the session information with sessionInfo().
> I found there is still nlme package in "loaded via a namespace (and
> not attached)".  Is it still causing problem?
> 
> Here is what I did:
> 
> R version 2.15.0 (2012-03-30)
> Copyright (C) 2012 The R Foundation for Statistical Computing
> ISBN 3-900051-07-0
> Platform: i386-pc-mingw32/i386 (32-bit)
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>   Natural language support but running in an English locale
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> Type 'demo()' for some demos, 'help()' for on-line help, or
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> Type 'q()' to quit R.
> 
> [Previously saved workspace restored]
> 
> > df <- bcwrear1
> > y <- df$day10
> > trial <- df$trial
> > block <- df$block
> > trt <- df$turf
> > library(lme4)
> Loading required package: Matrix
> Loading required package: lattice
> 
> Attaching package: ‘lme4’
> 
> The following object(s) are masked from ‘package:stats’:
> 
>     AIC, BIC
> 
> > fm.lmer <- lmer(log10(day10) ~ trt + (1|trial/block/trt), data=df, na.action=na.omit)
> Error: length(f1) == length(f2) is not TRUE
> In addition: Warning messages:
> 1: In block:trial :
>   numerical expression has 92 elements: only the first used
> 2: In block:trial :
>   numerical expression has 92 elements: only the first used
> 3: In trt:(block:trial) :
>   numerical expression has 92 elements: only the first used
> 4: In block:trial :
>   numerical expression has 92 elements: only the first used
> 5: In block:trial :
>   numerical expression has 92 elements: only the first used
> >
> > sessionInfo()
> R version 2.15.0 (2012-03-30)
> Platform: i386-pc-mingw32/i386 (32-bit)
> 
> locale:
> [1] LC_COLLATE=English_United States.1252
> [2] LC_CTYPE=English_United States.1252
> [3] LC_MONETARY=English_United States.1252
> [4] LC_NUMERIC=C
> [5] LC_TIME=English_United States.1252
> 
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
> 
> other attached packages:
> [1] lme4_0.999375-42 Matrix_1.0-6     lattice_0.20-6
> 
> loaded via a namespace (and not attached):
> [1] grid_2.15.0   nlme_3.1-103  stats4_2.15.0
> 
> 
> 
> 
> Thanks!!!
> 
> Steve
> 
> 
> 
> 
> 
> 
> On Mon, Jun 25, 2012 at 1:01 PM, Douglas Bates <bates@stat.wisc.edu> wrote:
> > On Mon, Jun 25, 2012 at 12:41 PM, Steve Hong <emptican@gmail.com> wrote:
> >> Hi Prof. Bates,
> >>
> >> Thanks for replying.  Yes, I loaded both packages together and ran
> >> them.  I don't understand different/separate R 'session'?  Obviously,
> >> it seems not different versions (e.g., 2.15.0 vs. 2.14.0).  Could you
> >> rephrase what you meant by R 'session'?
> >
> > I mean to run R, load lme4 and fit the model.  Then quit R and restart
> > it, load nlme and fit that model.
> >
> >> On Mon, Jun 25, 2012 at 12:28 PM, Douglas Bates <bates@stat.wisc.edu> wrote:
> >>> Are you trying to load both the nlme and the lme4 packages at the same
> >>> time?  That can cause problems.  You are better off fitting the lmer
> >>> model in one R session and the lme model in another.
> >>>
> >>> On Mon, Jun 25, 2012 at 11:50 AM, Steve Hong <emptican@gmail.com> wrote:
> >>>> Thank all of you for replying to me.
> >>>>
> >>>> I tried lmer, lme, and SAS.  I was able to get outputs when I use
> >>>> 'lme' whereas no results from 'lmer'.  I don't know why.  Does anyone
> >>>> know what the warning message mean?  Outputs from  'lme' were similar
> >>>> with those from SAS.  Below is selected outputs from lmer, lme, and
> >>>> SAS, FYI.
> >>>>
> >>>> Thanks again,
> >>>>
> >>>> Steve Hong
> >>>>
> >>>>> fm.lmer <- lmer(y ~ trt + (1|trial/block/trt), data=df, na.action=na.omit)
> >>>> Error: length(f1) == length(f2) is not TRUE
> >>>> In addition: Warning messages:
> >>>> 1: In block:trial :
> >>>>   numerical expression has 92 elements: only the first used
> >>>> 2: In block:trial :
> >>>>   numerical expression has 92 elements: only the first used
> >>>> 3: In trt:(block:trial) :
> >>>>   numerical expression has 92 elements: only the first used
> >>>> 4: In block:trial :
> >>>>   numerical expression has 92 elements: only the first used
> >>>> 5: In block:trial :
> >>>>   numerical expression has 92 elements: only the first used
> >>>>> fm.lme <- lme(y ~ trt, random=(~1|trial/block/trt), data = df, na.action=na.omit)
> >>>>> summary(fm.lme)
> >>>> Linear mixed-effects model fit by REML
> >>>>  Data: df
> >>>>         AIC       BIC   logLik
> >>>>   -85.22388 -60.68041 52.61194
> >>>>
> >>>> Random effects:
> >>>>  Formula: ~1 | trial
> >>>>         (Intercept)
> >>>> StdDev:   0.1112442
> >>>>
> >>>>  Formula: ~1 | block %in% trial
> >>>>          (Intercept)
> >>>> StdDev: 1.449228e-06
> >>>>
> >>>>  Formula: ~1 | trt %in% block %in% trial
> >>>>         (Intercept)  Residual
> >>>> StdDev:  0.07081356 0.1020226
> >>>>
> >>>> Fixed effects: y ~ trt
> >>>>                   Value  Std.Error DF    t-value p-value
> >>>> (Intercept)  0.24428523 0.08793775 56  2.7779337  0.0074
> >>>> trtau2      -0.00996643 0.05605221 25 -0.1778063  0.8603
> >>>> trtberm     -0.12786905 0.05686903 25 -2.2484830  0.0336
> >>>> trtls44      0.12326637 0.05478364 25  2.2500582  0.0335
> >>>> trtsr10y5    0.02513355 0.05517460 25  0.4555275  0.6527
> >>>> trtsr10y6    0.01932992 0.05478364 25  0.3528410  0.7272
> >>>>  Correlation:
> >>>>           (Intr) trtau2 trtbrm trtl44 trt105
> >>>> trtau2    -0.314
> >>>> trtberm   -0.309  0.486
> >>>> trtls44   -0.321  0.504  0.497
> >>>> trtsr10y5 -0.319  0.500  0.493  0.511
> >>>> trtsr10y6 -0.321  0.504  0.497  0.515  0.511
> >>>>
> >>>> Standardized Within-Group Residuals:
> >>>>           Min            Q1           Med            Q3           Max
> >>>> -2.614096e+00 -5.666986e-01 -9.727356e-05  4.692685e-01  2.410879e+00
> >>>>
> >>>> Number of Observations: 92
> >>>> Number of Groups:
> >>>>                     trial          block %in% trial trt %in% block %in% trial
> >>>>                         2                         6                        36
> >>>>> anova(fm.lme)
> >>>>             numDF denDF  F-value p-value
> >>>> (Intercept)     1    56 9.907983  0.0026
> >>>> trt             5    25 4.122070  0.0072
> >>>>
> >>>>
> >>>> SAS code and outputs:
> >>>> proc glimmix data=df;
> >>>> model y=trt;
> >>>> random trial block(trial) turf(block*turf);
> >>>> run;
> >>>>
> >>>>     Covariance Parameter Estimates
> >>>>
> >>>>                                 Standard
> >>>> Cov Parm             Estimate       Error
> >>>>
> >>>> trial                 0.01237     0.01823
> >>>> block(trial)                0           .
> >>>> trt(trial*block)    0.005015    0.002546
> >>>> Residual              0.01041    0.001963
> >>>>
> >>>>
> >>>>        Type III Tests of Fixed Effects
> >>>>
> >>>>              Num      Den
> >>>> Effect         DF       DF    F Value    Pr > F
> >>>>
> >>>> trt            5       25       4.12    0.0072
> >>>>
> >>>>
> >>>>
> >>>> On Mon, Jun 25, 2012 at 10:25 AM, Kevin Wright <kw.stat@gmail.com> wrote:
> >>>>>
> >>>>> This could be similar to a multi-location RCB design were "trial" is
> >>>>> location.  Since no distribution is specified, the distribution is
> >>>>> assumed to be Gaussian.  Make sure that trial, block, trt are factors,
> >>>>> this should be similar to SAS:
> >>>>>
> >>>>> lmer(y ~ trt + (1|trial/block/trt), data=df)
> >>>>>
> >>>>> > proc glimmix data=df;
> >>>>> > class trial block trt;
> >>>>> > model y=trt;
> >>>>> > random trial block(trial) trt(block*trial);
> >>>>>
> >>>>> Kevin Wright
> >>>>
> >>>> _______________________________________________
> >>>> R-sig-mixed-models@r-project.org mailing list
> >>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> 
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