> summary(big20.rcr1)
Linear mixed-effects model fit by REML
 Data: NULL 
       AIC      BIC    logLik
  4105.031 4122.896 -2048.516

Random effects:
 Formula: ~0 + minutes | player_id
          minutes Residual
StdDev: 0.0635688 5.640528

Fixed effects: points ~ minutes 
                 Value Std.Error  DF   t-value p-value
(Intercept) -2.6411425 1.2754322 624 -2.070782  0.0388
minutes      0.5911134 0.0424749 624 13.916764  0.0000
 Correlation: 
        (Intr)
minutes -0.928

Standardized Within-Group Residuals:
        Min          Q1         Med          Q3         Max 
-2.65660656 -0.68868388 -0.03207019  0.61335420  3.50984372 

Number of Observations: 645
Number of Groups: 20 
> 
> random.effects(big20.rcr1)
        minutes
1   0.147194828
2   0.050750300
3   0.058664523
4   0.069043739
5   0.025511981
6   0.017228086
7   0.012918292
8   0.061212356
9  -0.017264861
10 -0.001445245
11  0.013302621
12 -0.036365168
13 -0.051118273
14 -0.034977912
15 -0.031759933
16 -0.033011110
17 -0.056998020
18 -0.068410087
19 -0.039736160
20 -0.084739959
> 
> library(lme4)
> library(lattice)
> require(optimx)
> 
> xyplot(points ~ minutes | player_id)
> 
> big20.rcr2 <- lmer(points~ minutes + 
+ (0 + minutes|player_id),REML=TRUE) 
> 
> # control=lmerControl(opt="optimx",optCtrl  = list(method="nlminb")))
> 
> summary(big20.rcr2)
Linear mixed model fit by REML ['lmerMod']
Formula: points ~ minutes + (0 + minutes | player_id)

REML criterion at convergence: 4097

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-2.6566 -0.6887 -0.0321  0.6134  3.5098 

Random effects:
 Groups    Name    Variance  Std.Dev.
 player_id minutes  0.004041 0.06357 
 Residual          31.815557 5.64053 
Number of obs: 645, groups:  player_id, 20

Fixed effects:
            Estimate Std. Error t value
(Intercept) -2.64114    1.27543  -2.071
minutes      0.59111    0.04247  13.917

Correlation of Fixed Effects:
        (Intr)
minutes -0.928
> 
> random.effects(big20.rcr2)
$player_id
        minutes
1   0.147194829
2   0.050750300
3   0.058664524
4   0.069043739
5   0.025511981
6   0.017228086
7   0.012918293
8   0.061212356
9  -0.017264861
10 -0.001445245
11  0.013302622
12 -0.036365168
13 -0.051118274
14 -0.034977912
15 -0.031759933
16 -0.033011110
17 -0.056998021
18 -0.068410088
19 -0.039736160
20 -0.084739960

>