R version 2.7.0 Under development (unstable) (2008-01-17 r44028)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> library(lme4)
Loading required package: Matrix
Loading required package: lattice

Attaching package: 'Matrix'


	The following object(s) are masked from package:stats :

	 xtabs 

> 
> srrs2 <-
+     read.table("http://www.stat.columbia.edu/~gelman/arm/examples/radon/srrs2.dat",
+                header = TRUE, sep=",")
>                # Strip trailing blanks and capitalize county names.
> levels(srrs2$county) <- gsub("(\\w)(\\w*)", "\\U\\1\\L\\2",
+                              sub('[[:space:]]+$', '', levels(srrs2$county)),
+                              perl=TRUE)
>                # Use pmax to define the log radon
> srrs2$log.radon <- log(pmax(srrs2$activity, 0.1))
>                # Define floor as a factor with meaningful labels
> srrs2$floor[srrs2$floor == 9] <- NA
> srrs2$floor <- factor(srrs2$floor, labels = c("bsmnt", "1st", "2nd", "3rd"))
> 
> (M1<-lmer(log.radon ~ 1 + floor + (1|county), srrs2, subset = state == "MN"))
Linear mixed model fit by REML 
Formula: log.radon ~ 1 + floor + (1 | county) 
   Data: srrs2 
 Subset: state == "MN" 
  AIC  BIC logLik deviance REMLdev
 2177 2192  -1086     2164    2171
Random effects:
 Groups   Name        Variance Std.Dev.
 county   (Intercept) 0.10771  0.32819 
 Residual             0.57092  0.75559 
Number of obs: 919, groups: county, 85

Fixed effects:
            Estimate Std. Error t value
(Intercept)  1.46159    0.05157  28.340
floor1st    -0.69299    0.07043  -9.839

Correlation of Fixed Effects:
         (Intr)
floor1st -0.288
> ranef(M1)
An object of class “ranef.mer”
[[1]]
                  (Intercept)
Aitkin            -0.27006599
Anoka             -0.53393800
Becker             0.01761490
Beltrami           0.04290088
Benton            -0.01544452
Big Stone          0.01858295
Blue Earth         0.39650878
Brown              0.22115201
Carlton           -0.30150038
Carver             0.04700898
Cass              -0.02934816
Chippewa           0.11554290
Chisago           -0.22452334
Clay               0.37640720
Clearwater        -0.05909210
Cook              -0.21826655
Cottonwood        -0.08922393
Crow Wing         -0.24063972
Dakota            -0.11533157
Dodge              0.12242145
Douglas            0.16950564
Faribault         -0.44036531
Fillmore          -0.02064995
Freeborn           0.39894723
Goodhue            0.35194416
Hennepin          -0.09890608
Houston            0.16065520
Hubbard           -0.11481611
Isanti            -0.14659025
Itasca            -0.36159468
Jackson            0.27133290
Kanabec           -0.09689908
Kandiyohi          0.25817000
Kittson            0.03992963
Koochiching       -0.37453345
Lac Qui Parle      0.40643482
Lake              -0.66872284
Lake Of The Woods  0.16874168
Le Sueur           0.13638219
Lincoln            0.36441916
Lyon               0.30201145
Mahnomen          -0.01596964
Marshall           0.07888185
Martin            -0.24159875
Mcleod            -0.12406905
Meeker            -0.11988835
Mille Lacs        -0.16202612
Morrison          -0.19921040
Mower              0.16784183
Murray             0.16373379
Nicollet           0.30253935
Nobles             0.16845797
Norman            -0.07950325
Olmsted           -0.12875864
Otter Tail         0.08785802
Pennington        -0.13692876
Pine              -0.37378783
Pipestone          0.16878299
Polk               0.10597800
Pope              -0.04991567
Ramsey            -0.26204439
Redwood            0.25042769
Renville           0.07225594
Rice               0.25895528
Rock              -0.04451075
Roseau             0.13666335
Scott              0.23658540
Sherburne         -0.22349262
Sibley            -0.09424855
Stearns            0.02132103
Steele             0.07732212
Stevens            0.09044960
St Louis          -0.57164093
Swift             -0.20409713
Todd               0.09141911
Traverse           0.23222654
Wabasha            0.20267921
Wadena            -0.09073539
Waseca            -0.36711777
Washington        -0.12111301
Watonwan           0.44439533
Wilkin             0.12196102
Winona             0.11008563
Wright             0.12903053
Yellow Medicine   -0.07535666

> sqrt(as.vector(attr(ranef(M1, postVar = TRUE)[[1]], "postVar")))
 [1] 0.24776139 0.09981789 0.26226150 0.21543965 0.24776139 0.26226150
 [7] 0.17198992 0.24776139 0.19316763 0.22476988 0.23542779 0.24776139
[13] 0.22476988 0.17198992 0.24776139 0.27964703 0.24776139 0.18165941
[19] 0.09142725 0.26226150 0.19980737 0.22476988 0.27964703 0.19980737
[25] 0.17198992 0.07194472 0.22476988 0.23542779 0.26226150 0.18714866
[31] 0.23542779 0.24776139 0.24776139 0.26226150 0.21543965 0.27964703
[37] 0.19980737 0.24776139 0.23542779 0.24776139 0.20718251 0.30102240
[43] 0.19980737 0.21543965 0.17662646 0.23542779 0.27964703 0.19980737
[49] 0.17662646 0.30102240 0.24776139 0.26226150 0.26226150 0.14203336
[55] 0.20718251 0.26226150 0.22476988 0.24776139 0.24776139 0.27964703
[61] 0.12371723 0.23542779 0.26226150 0.18714866 0.27964703 0.17198992
[67] 0.17662646 0.20718251 0.24776139 0.13726586 0.19316763 0.27964703
[73] 0.06860509 0.24776139 0.26226150 0.24776139 0.21543965 0.23542779
[79] 0.24776139 0.10549376 0.26226150 0.30102240 0.17662646 0.17662646
[85] 0.27964703
> 
> proc.time()
   user  system elapsed 
 11.300   0.232  12.537