[R-sig-ME] sas to R

[Douglas Bates]

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
>
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