[R] different results from lme and lmer function

[li li]

Hi all,
  I am fitting a random slope and random intercept model using R. I
used both lme and lmer funciton for the same model. However I got
different results as shown below (different variance component
estimates and so on). I think that is really confusing. They should
produce close results. Anyone has any thoughts or suggestions. Also,
which one should be comparable to sas results?
 Thanks!
  Hanna

## using lme function
> mod_lme <- lme(ti  ~ type*months, random=~ 1+months|lot, na.action=na.omit,
+ data=one, control = lmeControl(opt = "optim"))
> summary(mod_lme)
Linear mixed-effects model fit by REML
 Data: one
        AIC       BIC   logLik
  -82.60042 -70.15763 49.30021

Random effects:
 Formula: ~1 + months | lot
 Structure: General positive-definite, Log-Cholesky parametrization
            StdDev       Corr
(Intercept) 8.907584e-03 (Intr)
months      6.039781e-05 -0.096
Residual    4.471243e-02

Fixed effects: ti ~ type * months
                     Value   Std.Error DF   t-value p-value
(Intercept)     0.25831245 0.016891587 31 15.292373  0.0000
type            0.13502089 0.026676101  4  5.061493  0.0072
months          0.00804790 0.001218941 31  6.602368  0.0000
type:months -0.00693679 0.002981859 31 -2.326329  0.0267
 Correlation:
               (Intr) typPPQ months
type           -0.633
months         -0.785  0.497
type:months  0.321 -0.762 -0.409

Standardized Within-Group Residuals:
          Min            Q1           Med            Q3           Max
-2.162856e+00 -1.962972e-01 -2.771184e-05  3.749035e-01  2.088392e+00

Number of Observations: 39
Number of Groups: 6




###Using lmer function
> mod_lmer <-lmer(ti  ~ type*months+(1+months|lot), na.action=na.omit, data=one)
> summary(mod_lmer)
Linear mixed model fit by REML t-tests use Satterthwaite approximations to
  degrees of freedom [merModLmerTest]
Formula: ti ~ type * months + (1 + months | lot)
   Data: one

REML criterion at convergence: -98.8

Scaled residuals:
    Min      1Q  Median      3Q     Max
-2.1347 -0.2156 -0.0067  0.3615  2.0840

Random effects:
 Groups   Name        Variance  Std.Dev.  Corr
 lot      (Intercept) 2.870e-04 0.0169424
          months      4.135e-07 0.0006431 -1.00
 Residual             1.950e-03 0.0441644
Number of obs: 39, groups:  lot, 6

Fixed effects:
                Estimate Std. Error        df t value Pr(>|t|)
(Intercept)     0.258312   0.018661  4.820000  13.842 4.59e-05 ***
type         0.135021   0.028880  6.802000   4.675  0.00245 **
months          0.008048   0.001259 11.943000   6.390 3.53e-05 ***
type:months -0.006937   0.002991 28.910000  -2.319  0.02767 *
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr) typPPQ months
type     -0.646
months      -0.825  0.533
type:month  0.347 -0.768 -0.421