R help - Mar 2013 - lmer (LME4) and survey standard error

Hello,

I am using lmer (LME4) to build a model from data for 19 different
neighborhoods drawn, in part, from the American Communities Survey
(ACS). The ACS data is static while other variables change over the
five years under investigation. I am new to mixed effects models and
was hoping that someone could suggest a way to include the ACS
standard error for each covariate into the model. I currently call
lmer as follows:

#Y = dependent variable (numeric, vector)
#G = neighborhood names (string, vector)
#X = independent variables (numeric, matrix)

m = lmer(Y ~ (1|G) + X)

Thank you,
-david

David Epstein <davideps <at> umich.edu> writes:

[snip]
> I am using lmer (LME4) to build a model from data for 19 different
> neighborhoods drawn, in part, from the American Communities Survey
> (ACS). The ACS data is static while other variables change over the
> five years under investigation. I am new to mixed effects models and
> was hoping that someone could suggest a way to include the ACS
> standard error for each covariate into the model. I currently call
> lmer as follows:
> 
> #Y = dependent variable (numeric, vector)
> #G = neighborhood names (string, vector)
> #X = independent variables (numeric, matrix)
> 
> m = lmer(Y ~ (1|G) + X)
> 
  [snip]

  I suggest (1) taking a look at the weights= argument to
see if it does what you need
and (2) asking this question on the r-sig-mixed-models list,
where there may be more expertise on this subject.

  Ben Bolker