Extrahieren ergibt sich aus einem `lmermod` Objekt

Question

Ich möchte einige Ergebnisse aus einer lmermod Objekt extrahieren

require(lme4) 
(fm1 <- lmer(Yield ~ 1|Batch, Dyestuff)) 

Dies erzeugt

Linear mixed model fit by REML ['lmerMod'] 
Formula: Yield ~ 1 | Batch 
    Data: Dyestuff 
REML criterion at convergence: 319.6543 
Random effects: 
Groups Name  Std.Dev. 
Batch (Intercept) 42.00 
Residual    49.51 
Number of obs: 30, groups: Batch, 6 
Fixed Effects: 
(Intercept) 
     1527 

Insbesondere würde Ich mag die Standard devations von extrahieren die 2 zufälligen Effekte, dh 42,00 und 49,51. Ich denke, es kann eine integrierte Methode, dies zu tun, aber ich konnte es nicht schnell finden, so dachte ich, soll ich in der Lage sein, es zu finden, indem str(fm1) mit, die diese produziert:

Formal class 'lmerMod' [package "lme4"] with 13 slots 
    ..@ resp :Reference class 'lmerResp' [package "lme4"] with 9 fields 
    .. ..$ Ptr :<externalptr> 
    .. ..$ mu  : num [1:30] 1510 1510 1510 1510 1510 ... 
    .. ..$ offset : num [1:30] 0 0 0 0 0 0 0 0 0 0 ... 
    .. ..$ sqrtXwt: num [1:30] 1 1 1 1 1 1 1 1 1 1 ... 
    .. ..$ sqrtrwt: num [1:30] 1 1 1 1 1 1 1 1 1 1 ... 
    .. ..$ weights: num [1:30] 1 1 1 1 1 1 1 1 1 1 ... 
    .. ..$ wtres : num [1:30] 35.1 -69.9 -69.9 10.1 70.1 ... 
    .. ..$ y  : num [1:30] 1545 1440 1440 1520 1580 ... 
    .. ..$ REML : int 1 
    .. ..and 26 methods, of which 14 are possibly relevant: 
    .. .. allInfo, copy#envRefClass, initialize, initialize#lmResp, 
    .. .. initializePtr, initializePtr#lmResp, objective, ptr, ptr#lmResp, 
    .. .. setOffset, setResp, setWeights, updateMu, wrss 
    ..@ Gp  : int [1:2] 0 6 
    ..@ call : language lmer(formula = Yield ~ 1 | Batch, data = Dyestuff) 
    ..@ frame :'data.frame':  30 obs. of 2 variables: 
    .. ..$ Yield: num [1:30] 1545 1440 1440 1520 1580 ... 
    .. ..$ Batch: Factor w/ 6 levels "A","B","C","D",..: 1 1 1 1 1 2 2 2 2 2 ... 
    .. ..- attr(*, "terms")=Classes 'terms', 'formula' length 3 Yield ~ 1 + Batch 
    .. .. .. ..- attr(*, "variables")= language list(Yield, Batch) 
    .. .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1 
    .. .. .. .. ..- attr(*, "dimnames")=List of 2 
    .. .. .. .. .. ..$ : chr [1:2] "Yield" "Batch" 
    .. .. .. .. .. ..$ : chr "Batch" 
    .. .. .. ..- attr(*, "term.labels")= chr "Batch" 
    .. .. .. ..- attr(*, "order")= int 1 
    .. .. .. ..- attr(*, "intercept")= int 1 
    .. .. .. ..- attr(*, "response")= int 1 
    .. .. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv> 
    .. .. .. ..- attr(*, "predvars")= language list(Yield, Batch) 
    .. .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "factor" 
    .. .. .. .. ..- attr(*, "names")= chr [1:2] "Yield" "Batch" 
    .. .. .. ..- attr(*, "predvars.fixed")= language list(Yield) 
    .. ..- attr(*, "formula")=Class 'formula' length 3 Yield ~ 1 | Batch 
    .. .. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv> 
    ..@ flist :List of 1 
    .. ..$ Batch: Factor w/ 6 levels "A","B","C","D",..: 1 1 1 1 1 2 2 2 2 2 ... 
    .. ..- attr(*, "assign")= int 1 
    ..@ cnms :List of 1 
    .. ..$ Batch: chr "(Intercept)" 
    ..@ lower : num 0 
    ..@ theta : num 0.848 
    ..@ beta : num 1527 
    ..@ u  : num [1:6] -20.755 0.461 33.669 -27.212 66.877 ... 
    ..@ devcomp:List of 2 
    .. ..$ cmp : Named num [1:10] 9.15 1.88 61495.41 9590.84 71086.25 ... 
    .. .. ..- attr(*, "names")= chr [1:10] "ldL2" "ldRX2" "wrss" "ussq" ... 
    .. ..$ dims: Named int [1:12] 30 30 1 29 1 6 1 1 0 1 ... 
    .. .. ..- attr(*, "names")= chr [1:12] "N" "n" "p" "nmp" ... 
    ..@ pp  :Reference class 'merPredD' [package "lme4"] with 18 fields 
    .. ..$ Lambdat:Formal class 'dgCMatrix' [package "Matrix"] with 6 slots 
    .. .. .. ..@ i  : int [1:6] 0 1 2 3 4 5 
    .. .. .. ..@ p  : int [1:7] 0 1 2 3 4 5 6 
    .. .. .. ..@ Dim  : int [1:2] 6 6 
    .. .. .. ..@ Dimnames:List of 2 
    .. .. .. .. ..$ : NULL 
    .. .. .. .. ..$ : NULL 
    .. .. .. ..@ x  : num [1:6] 0.848 0.848 0.848 0.848 0.848 ... 
    .. .. .. ..@ factors : list() 
    .. ..$ LamtUt :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots 
    .. .. .. ..@ i  : int [1:30] 0 0 0 0 0 1 1 1 1 1 ... 
    .. .. .. ..@ p  : int [1:31] 0 1 2 3 4 5 6 7 8 9 ... 
    .. .. .. ..@ Dim  : int [1:2] 6 30 
    .. .. .. ..@ Dimnames:List of 2 
    .. .. .. .. ..$ : NULL 
    .. .. .. .. ..$ : NULL 
    .. .. .. ..@ x  : num [1:30] 0.848 0.848 0.848 0.848 0.848 ... 
    .. .. .. ..@ factors : list() 
    .. ..$ Lind : int [1:6] 1 1 1 1 1 1 
    .. ..$ Ptr :<externalptr> 
    .. ..$ RZX : num [1:6, 1] 1.98 1.98 1.98 1.98 1.98 ... 
    .. ..$ Ut  :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots 
    .. .. .. ..@ i  : int [1:30] 0 0 0 0 0 1 1 1 1 1 ... 
    .. .. .. ..@ p  : int [1:31] 0 1 2 3 4 5 6 7 8 9 ... 
    .. .. .. ..@ Dim  : int [1:2] 6 30 
    .. .. .. ..@ Dimnames:List of 2 
    .. .. .. .. ..$ : chr [1:6] "A" "B" "C" "D" ... 
    .. .. .. .. ..$ : NULL 
    .. .. .. ..@ x  : num [1:30] 1 1 1 1 1 1 1 1 1 1 ... 
    .. .. .. ..@ factors : list() 
    .. ..$ Utr : num [1:6] 6384 6481 6634 6354 6787 ... 
    .. ..$ V  : num [1:30, 1] 1 1 1 1 1 1 1 1 1 1 ... 
    .. ..$ VtV : num [1, 1] 30 
    .. ..$ Vtr : num 45825 
    .. ..$ X  : num [1:30, 1] 1 1 1 1 1 1 1 1 1 1 ... 
    .. .. ..- attr(*, "dimnames")=List of 2 
    .. .. .. ..$ : chr [1:30] "1" "2" "3" "4" ... 
    .. .. .. ..$ : chr "(Intercept)" 
    .. .. ..- attr(*, "assign")= int 0 
    .. ..$ Xwts : num [1:30] 1 1 1 1 1 1 1 1 1 1 ... 
    .. ..$ Zt  :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots 
    .. .. .. ..@ i  : int [1:30] 0 0 0 0 0 1 1 1 1 1 ... 
    .. .. .. ..@ p  : int [1:31] 0 1 2 3 4 5 6 7 8 9 ... 
    .. .. .. ..@ Dim  : int [1:2] 6 30 
    .. .. .. ..@ Dimnames:List of 2 
    .. .. .. .. ..$ : chr [1:6] "A" "B" "C" "D" ... 
    .. .. .. .. ..$ : NULL 
    .. .. .. ..@ x  : num [1:30] 1 1 1 1 1 1 1 1 1 1 ... 
    .. .. .. ..@ factors : list() 
    .. ..$ beta0 : num 0 
    .. ..$ delb : num 1527 
    .. ..$ delu : num [1:6] -20.755 0.461 33.669 -27.212 66.877 ... 
    .. ..$ theta : num 0.848 
    .. ..$ u0  : num [1:6] 0 0 0 0 0 0 
    .. ..and 42 methods, of which 30 are possibly relevant: 
    .. .. b, beta, CcNumer, copy#envRefClass, initialize, initializePtr, 
    .. .. installPars, L, ldL2, ldRX2, linPred, P, ptr, RX, RXdiag, RXi, 
    .. .. setBeta0, setDelb, setDelu, setTheta, solve, solveU, sqrL, u, unsc, 
    .. .. updateDecomp, updateL, updateLamtUt, updateRes, updateXwts 
    ..@ optinfo:List of 7 
    .. ..$ optimizer: chr "bobyqa" 
    .. ..$ control :List of 1 
    .. .. ..$ iprint: int 0 
    .. ..$ derivs :List of 2 
    .. .. ..$ gradient: num 1.61e-07 
    .. .. ..$ Hessian : num [1, 1] 14.1 
    .. ..$ conv  :List of 2 
    .. .. ..$ opt : int 0 
    .. .. ..$ lme4: list() 
    .. ..$ feval : int 16 
    .. ..$ warnings : list() 
    .. ..$ val  : num 0.848 

... aber das lässt mich nicht weiser.

Answer 1

lme4 liefert VarCorr für Varianz und Korrelationskomponenten zu extrahieren:

varcor <- VarCorr(fm1) 
as.data.frame(varcor) 
#  grp  var1 var2 vcov sdcor 
#1 Batch (Intercept) <NA> 1764.05 42.0006 
#2 Residual  <NA> <NA> 2451.25 49.5101