[R-sig-ME] Extracting means and SEs from an lmer object

[Douglas Bates]

On Mon, Feb 6, 2012 at 4:26 PM, Chris Eckert <chris.eckert at queensu.ca> wrote:
> Hi,
> I am trying to extract means and SEs from an lmer object.
> So, I followed the example code from http://glmm.wikidot.com/faq
> from the "Predictions and/or confidence (or prediction) intervals on predictions" section of the faq

> library(lme4)
> library(ggplot2) # Plotting
> library(MEMSS) # for Orthodont

The problem may be due to MEMSS bringing in other packages that mask
the definition of fixef in lme4.  It works for me (see enclosed) if I
use
data(Orthodont, package="MEMSS")
instead.

> fm1 = lmer(
>    formula = distance ~ age*Sex + (age|Subject)
>    , data = Orthodont
> )
> newdat <- expand.grid(
>    age=c(8,10,12,14)
>    , Sex=c("Male","Female")
>    , distance = 0
> )
> mm = model.matrix(terms(fm1),newdat)
> newdat$distance = mm %*% fixef(fm1)
> pvar1 <- diag(mm %*% tcrossprod(vcov(fm1),mm))
> tvar1 <- pvar1+VarCorr(fm1)$Subject[1]
> newdat <- data.frame(
>    newdat
>    , plo = newdat$distance-2*sqrt(pvar1)
>    , phi = newdat$distance+2*sqrt(pvar1)
>    , tlo = newdat$distance-2*sqrt(tvar1)
>    , thi = newdat$distance+2*sqrt(tvar1)
> )
> When I get to the "newdat$distance = mm %*% fixef(fm1)" I get the following error:
> "Error in UseMethod("fixef") :
>  no applicable method for 'fixef' applied to an object of class "mer""
>
> I am using lme4 version version 0.999375-42 (the most recent version on Cran) with R version 2.14.0
>
> Any explanation for this would be greatly appreciated.
>
> Chris Eckert
> Department of Biology
> Queen's University
> Kingston, Ontario, Canada

Seeing that makes me nostalgic. I spend my formative years at Queen's.
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R version 2.14.1 (2011-12-22)
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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:base?:

    det


Attaching package: ?lme4?

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

    AIC, BIC

> library(ggplot2) # Plotting
Loading required package: reshape
Loading required package: plyr

Attaching package: ?reshape?

The following object(s) are masked from ?package:plyr?:

    rename, round_any

The following object(s) are masked from ?package:Matrix?:

    expand

Loading required package: grid
Loading required package: proto
> sessionInfo()
R version 2.14.1 (2011-12-22)
Platform: x86_64-pc-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=C                 LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
[1] ggplot2_0.8.9    proto_0.3-9.2    reshape_0.8.4    plyr_1.7.1      
[5] lme4_0.999375-42 Matrix_1.0-3     lattice_0.20-0  

loaded via a namespace (and not attached):
[1] nlme_3.1-103  stats4_2.14.1
> data(Orthodont, package="MEMSS")
> fm1 <- lmer(
+    formula = distance ~ age*Sex + (age|Subject)
+    , data = Orthodont
+ )
> fixef(fm1)
(Intercept)         age     SexMale age:SexMale 
 17.3727273   0.4795455  -1.0321023   0.3048295 
> newdat <- expand.grid(
+    age=c(8,10,12,14)
+    , Sex=c("Male","Female")
+    , distance = 0
+ )
> mm <- model.matrix(terms(fm1),newdat)
> newdat$distance <- mm %*% fixef(fm1)
> pvar1 <- diag(mm %*% tcrossprod(vcov(fm1),mm))
> tvar1 <- pvar1+VarCorr(fm1)$Subject[1]
> newdat <- data.frame(
+    newdat
+    , plo = newdat$distance-2*sqrt(pvar1)
+    , phi = newdat$distance+2*sqrt(pvar1)
+    , tlo = newdat$distance-2*sqrt(tvar1)
+    , thi = newdat$distance+2*sqrt(tvar1)
+ )
> 
> proc.time()
   user  system elapsed 
  4.136   0.800   4.031