[R-sig-ME] sas to R

Steve Hong emptican at gmail.com
Mon Jun 25 21:03:02 CEST 2012


Thank you, all.

I restarted R and checked package list using 'search()'.  And then,
loaded 'lme4' and ran the model.  However, the results are same...

Below is what I did.

Thank you much again!!!

Steve




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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

[Previously saved workspace restored]

> search()
[1] ".GlobalEnv"        "package:stats"     "package:graphics"
[4] "package:grDevices" "package:utils"     "package:datasets"
[7] "package:methods"   "Autoloads"         "package:base"
> library(lme4)
Loading required package: Matrix
Loading required package: lattice

Attaching package: ‘lme4’

The following object(s) are masked from ‘package:stats’:

    AIC, BIC

> search()
 [1] ".GlobalEnv"        "package:lme4"      "package:Matrix"
 [4] "package:lattice"   "package:stats"     "package:graphics"
 [7] "package:grDevices" "package:utils"     "package:datasets"
[10] "package:methods"   "Autoloads"         "package:base"
> bcwrear1 <- read.table("C:/bcwrear1.txt", header=T)
> df <- bcwrear1
> df=bcwrear1
> df=transform(df, y=day10, trt=turf)
> fm.lmer <- lmer(log10(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
>



On Mon, Jun 25, 2012 at 1:36 PM, Jake Westfall <jake987722 at hotmail.com> wrote:
>
> You can unload nlme by using:
> detach("package:nlme")
>
>
> Jake
>
>> Date: Mon, 25 Jun 2012 13:12:52 -0500
>> From: emptican at gmail.com
>> To: bates at stat.wisc.edu
>> CC: r-sig-mixed-models at 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)
>>
>> R is free software and comes with ABSOLUTELY NO WARRANTY.
>> You are welcome to redistribute it under certain conditions.
>> Type 'license()' or 'licence()' for distribution details.
>>
>>   Natural language support but running in an English locale
>>
>> R is a collaborative project with many contributors.
>> Type 'contributors()' for more information and
>> 'citation()' on how to cite R or R packages in publications.
>>
>> Type 'demo()' for some demos, 'help()' for on-line help, or
>> 'help.start()' for an HTML browser interface to help.
>> 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 at stat.wisc.edu> wrote:
>> > On Mon, Jun 25, 2012 at 12:41 PM, Steve Hong <emptican at 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 at 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 at 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 at 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 at r-project.org mailing list
>> >>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
>> _______________________________________________
>> R-sig-mixed-models at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
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