[R] Rounding of lme coefficients: Mac vs Windows

[David Afshartous]

All,

I have an lme model estimated in R 2.5.1 on my Mac; when I estimate the same
model on Windows, the parameter coefficients are rounded to integers.  Below
is a similar example for the Orthodont data.  Is there some option I need to
set in the Windows version to prevent rounding?  Didn't see this in the
archives.

Thanks,
David Afshartous


> sessionInfo()
R version 2.5.1 (2007-06-27)
i386-apple-darwin8.9.1

locale:
en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] "stats"     "graphics"  "grDevices" "utils"     "datasets"  "methods"
"base"     

other attached packages:
    nlme 
"3.1-84" 
> fm1 <- lme(distance ~ age, data = Orthodont) # random is ~ age
> 
> fm1
Linear mixed-effects model fit by REML
  Data: Orthodont 
  Log-restricted-likelihood: -221.3183
  Fixed: distance ~ age
(Intercept)         age
 16.7611111   0.6601852

Random effects:
 Formula: ~age | Subject
 Structure: General positive-definite
            StdDev    Corr
(Intercept) 2.3270338 (Intr)
age         0.2264276 -0.609
Residual    1.3100399

Number of Observations: 108
Number of Groups: 27


> sessionInfo()
R version 2.6.0 (2007-10-03)
i386-pc-mingw32 

locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] nlme_3.1-85       foreign_0.8-23    arm_1.0-33        R2WinBUGS_2.1-6
[5] coda_0.12-1       lme4_0.99875-8    Matrix_0.999375-2 lattice_0.16-5
[9] MASS_7.2-36   

loaded via a namespace (and not attached):
[1] grid_2.6.0  tools_2.6.0
> fm1 <- lme(distance ~ age, data = Orthodont) # random is ~ age
> fm1
Linear mixed-effects model fit by REML
  Data: Orthodont 
  Log-restricted-likelihood: -221
  Fixed: distance ~ age
(Intercept)         age
      16.76        0.66

Random effects:
 Formula: ~age | Subject
 Structure: General positive-definite
            StdDev Corr
(Intercept) 2.33   (Intr)
age         0.23   -0.61
Residual    1.31  

Number of Observations: 108
Number of Groups: 27
>