R version 3.2.3 beta (2015-11-29 r69717) -- "Wooden Christmas-Tree"
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> library(nlme)
> fm1 <- lmList(Oxboys)
> fm1
Call:
  Model: height ~ age | Subject 
   Data: Oxboys 

Coefficients:
   (Intercept)      age
10    130.2616 3.722915
26    137.9927 5.588783
25    139.2105 4.024081
9     138.1369 6.009057
2     142.8584 5.440176
6     146.7908 3.963171
7     146.1279 4.990050
17    142.9777 8.611780
16    147.5447 4.545196
15    144.2759 7.124260
8     148.2929 6.464712
20    151.4707 4.374466
1     148.1203 7.178151
18    151.1804 5.957793
5     151.4293 6.246128
23    151.0645 7.185123
11    150.0467 8.506082
21    150.5210 7.497794
3     155.6508 4.774669
24    153.1404 6.764705
22    154.5670 8.087514
12    156.8106 7.015468
13    156.0714 8.493806
14    159.4738 8.670886
19    164.5761 9.065620
4     165.0724 9.360561

Degrees of freedom: 234 total; 182 residual
Residual standard error: 0.6598878
> fm2 <- lme(fm1)
> fm2
Linear mixed-effects model fit by REML
  Data: Oxboys 
  Log-restricted-likelihood: -362.0455
  Fixed: height ~ age 
(Intercept)         age 
 149.371753    6.525469 

Random effects:
 Formula: ~age | Subject
 Structure: General positive-definite, Log-Cholesky parametrization
            StdDev   Corr  
(Intercept) 8.081077 (Intr)
age         1.680717 0.641 
Residual    0.659889       

Number of Observations: 234
Number of Groups: 26 
> vc2 <- VarCorr(fm2)
> stopifnot(
+     all.equal(fixef(fm2), c("(Intercept)" = 149.371753,
+                             age = 6.52546866), tol=1e-8),
+     all.equal(as.numeric(vc2[,"StdDev"]),
+               c(8.081077, 1.680717, 0.659889), tol=4e-7))
> 
> # bug report from Arne.Mueller@sanofi-aventis.com
> mod <- distance ~ age + Sex
> fm3 <- lme(mod, Orthodont, random = ~ 1)
> pm3 <- predict(fm3, Orthodont)
> stopifnot(all.equal(mean(pm3), 24.023148148),
+ 	  all.equal(  sd(pm3), 2.4802195115),
+ 	  all.equal(quantile(pm3), c("0%"  = 17.0817792, "25%" = 22.3481813,
+ 				     "50%" = 23.9271016, "75%" = 25.5740014,
+ 				     "100%"= 30.8662241)))
> 
> 
> ## bug report and fix from Dimitris Rizopoulos and Spencer Graves:
> ## when 'returnObject = TRUE', do not stop() but give warning() on non-convergence:
> tools::assertWarning(
+ fm1 <- lme(distance ~ age, data = Orthodont,
+ 	   control = lmeControl(msMaxIter = 1, returnObject = TRUE))
+ )
> 
> ## based on bug report on R-help
> (p3.1 <- predict(fm3, Orthodont[1,]))
     M01 
25.39237 
attr(,"label")
[1] "Predicted values (mm)"
> # failed in 3.1-88
> stopifnot(all.equal(pm3[1], p3.1,
+ 		    check.attributes=FALSE, tolerance = 1e-14))
> 
> ## Intervals failed in a patch proposal (Nov.2015):
> (fm4 <- lme(distance ~ age, Orthodont, random = ~ age | Subject))
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, Log-Cholesky parametrization
            StdDev    Corr  
(Intercept) 2.3270341 (Intr)
age         0.2264278 -0.609
Residual    1.3100397       

Number of Observations: 108
Number of Groups: 27 
> (i4 <- intervals(fm4))
Approximate 95% confidence intervals

 Fixed effects:
                 lower       est.      upper
(Intercept) 15.2183224 16.7611111 18.3038999
age          0.5183867  0.6601852  0.8019837
attr(,"label")
[1] "Fixed effects:"

 Random Effects:
  Level: Subject 
                          lower       est.     upper
sd((Intercept))       0.9485605  2.3270341 5.7087424
sd(age)               0.1025090  0.2264278 0.5001467
cor((Intercept),age) -0.9382505 -0.6093329 0.2981686

 Within-group standard error:
   lower     est.    upper 
1.084977 1.310040 1.581788 
> reSS <- data.frame(lower = c(0.9485605, 0.10250901, -0.93825047),
+                    est.  = c(2.3270341, 0.22642779, -0.60933286),
+                    upper = c(5.7087424, 0.50014674,  0.29816857))
> rownames(reSS) <- rownames(i4$reStruct$Subject)
> sm4 <- summary(fm4)
> stopifnot(
+     all.equal(fixef(fm4),
+               c("(Intercept)" = 16.761111, age = 0.66018519)),
+     identical(fixef(fm4), sm4$tTable[,"Value"]),
+     all.equal(sm4$tTable[,"Std.Error"],
+               c("(Intercept)" = 0.77524603, age = 0.071253264), tol=6e-8),
+     all.equal(i4$reStruct$Subject[,"est."], reSS[,"est."], tol= 8e-8)
+     ## (lower, upper) cannot be very accurate for these : ==> tol = *e-4
+    ,
+     all.equal(i4$reStruct$Subject[,c(1,3)], reSS[,c(1,3)], tol= 8e-4)
+    ,
+     all.equal(as.vector(i4$sigma),
+               ##  lower     est.        upper
+               c(1.0849772, 1.3100397, 1.5817881), tol=8e-4)
+ )
> 
> 
> ## wrong results from getData:
> load("ss2.rda")
> m1 <- lme(PV1MATH ~  ESCS + Age +time ,
+           random = ~   time|SCHOOLID,
+           data = ss2,
+           weights = varIdent(form=~1|time),
+           corr = corCompSymm(form=~1|SCHOOLID/StIDStd),
+           na.action = na.omit)
> plot(m1, resid(.) ~ WEALTH)
> 
> m2 <- lme(PV1MATH ~  ESCS + Age +time ,
+           random = ~   time|SCHOOLID,
+           data = ss2,
+           weights = varIdent(form=~1|time),
+           corr = corCompSymm(form=~1|SCHOOLID/StIDStd),
+           na.action = na.omit)
> plot(m2, resid(.) ~ WEALTH)
> 
> proc.time()
   user  system elapsed 
   1.97    0.08    2.13