[R] weights argument in the lmer function in lme4

[Spencer Graves]

	  I agree:  The lmer weights argument seems not to have any effect.  To 
check this, I modified the first example in the "lmer" documentation as 
follows:

Sleep <- sleepstudy
Sleep$wts <- 1:180
(fm1 <- lmer(Reaction ~ Days + (Days|Subject), Sleep))
(fm1w <- lmer(Reaction ~ Days + (Days|Subject),
                      weights=wts, Sleep))

	  The numbers from both seemed to be the same.  To try to help diagnose 
this, I listed "lmer", and found that it consisted of a call to 
"standardGeneric".  Then 'getMethods("lmer")' listed only one "method" 
for the case where the argument "formula" had class "formula".  I tried 
to trace this further, e.g., by giving it a different name and using 
"debug".  After being stopped a couple of time by functions hidden in 
the "Matrix" namespace, I gave ups.

	  However, at least you know that it's not you.  And I've included Doug 
Bates as a "cc" so he can use this info as he sees fit.

	  hope this helps.
	  spencer graves
	
 > sessionInfo()
R version 2.2.1, 2005-12-20, i386-pc-mingw32

attached base packages:
[1] "methods"   "stats"     "graphics"  "grDevices" "utils"     "datasets"
[7] "base"

other attached packages:
      lme4   lattice    Matrix
"0.995-2" "0.12-11" "0.995-4"
 > 	

Patrick Connolly wrote:

> I suspect the weights argument is not having any effect.
> 
> Package:              Matrix
> Version:              0.995-2
> Date:                 2006-01-19
> 
> 
> Beginning with this:
> 
> Browse[1]>   resp.lmer <- lmer(SensSSC ~ Block + Season + (1 | Plot) + (1 | Ma) + (1 | Pa) + 
> +     (1 | MaPa), weights = SensSSC.N, data = xx)
> 
> I group the output into a table with my ran.eff function and get this:
> 
> Browse[1]> ran.eff(resp.lmer)
>           01     02     03     04     05     06     07   GCAf RankF
> A     13.714 13.709 13.886 14.124 15.120 13.546 14.586  0.472     1
> B     13.452     NA 13.426 13.632 14.439 13.512 13.713  0.069     3
> C     13.922 13.770 14.353     NA 14.661 13.529 14.367  0.453     2
> D         NA     NA 13.353     NA     NA     NA     NA -0.051     4
> E     12.775 12.767 12.823 12.767 14.036 12.631 13.645 -0.495     6
> F     13.043 13.338 12.641 12.977 13.848 12.425 13.530 -0.448     5
> GCAm  -0.200 -0.169 -0.165 -0.103  0.736 -0.428  0.329     NA    NA
> RankM  6.000  5.000  4.000  3.000  1.000  7.000  2.000     NA    NA
> 
> 
> Despite any shortcomings in my ran.eff function, those values look
> alright, but they're the same (to any number of decimal places) as I'd
> get without a weights argument.  Just to check that the weights really
> don't effect it, I tried using only the rows with a weight of 5
> (almost 90% of the data) but it was substantially different.
> 
> Browse[1]>   resp.lmer5 <- lmer(SensSSC ~ Block + Season + (1 | Plot) + (1 | Ma) + (1 | Pa) + 
> +     (1 | MaPa), subset = SensSSC.N == 5, data = xx)
> 
> Browse[1]> ran.eff(resp.lmer5)
>           01     02     03     04     05     06     07   GCAf RankF
> A     13.435 13.349 13.595 13.914 14.722 13.161 14.414  0.345     2
> B     13.068     NA 13.110 13.447 14.121 13.296 13.637 -0.014     4
> C     13.702 13.537 14.256     NA 14.371 13.575 14.247  0.469     1
> D         NA     NA 13.276     NA     NA     NA     NA -0.001     3
> E     12.717 12.659 12.786 12.719 13.642 12.659 13.556 -0.425     6
> F     13.015 13.101 12.549 12.920 13.629 12.438 13.474 -0.374     5
> GCAm  -0.210 -0.230 -0.146 -0.049  0.596 -0.353  0.391     NA    NA
> RankM  5.000  6.000  4.000  3.000  1.000  7.000  2.000     NA    NA
> 
> That seems to indicate that weights cannot be readily ignored.
> 
> Has anyone had experience to indicate that the weights argument does
> produce a difference, and so I should be looking somewhere else for
> the reason why I'm getting such results?
> 
> 
> TIA
>