> lCtr <- lmeControl(maxIter = 5000, niterEM = 500, msMaxIter=1000, msMaxEval=1000, msVerbose = FALSE, opt = 'optim')
> lev.lm <- lme(data ~ des_days, random = ~des_days|ratID, data=data_red_trf, na.action=na.omit, method = "ML", control=lCtr)
> summary(lev.lm)

Linear mixed-effects model fit by maximum likelihood
 Data: data_red_trf
        AIC       BIC   logLik
  -3289.891 -3216.717 1659.946

Random effects:
 Formula: ~des_days | ratID
 Structure: General positive-definite, Log-Cholesky parametrization
            StdDev      Corr
(Intercept) 0.018205256 (Intr) ds_dy1 ds_d14
des_days1   0.014267902 -0.116
des_days14  0.012291117  0.289  0.916
des_days48  0.009514837 -0.866 -0.393 -0.725
Residual    0.043158947

Fixed effects: data ~ des_days
                 Value   Std.Error  DF   t-value p-value
(Intercept)  0.8274313 0.007937938 962 104.23757  0.0000
des_days1   -0.0026322 0.007443294 962  -0.35363  0.7237
des_days14  -0.0011319 0.006635512 962  -0.17058  0.8646
des_days48   0.0112579 0.005452614 962   2.06469  0.0392
 Correlation:
           (Intr) ds_dy1 ds_d14
des_days1  -0.213
des_days14  0.068  0.694
des_days48 -0.738 -0.078 -0.208

Standardized Within-Group Residuals:
         Min           Q1          Med           Q3          Max
-4.692631026 -0.524900364  0.006026586  0.514647345  3.766144781

Number of Observations: 971
Number of Groups: 6