Dear R help,
Does no one have an idea of where I might find information that could help
me with this problem? I apologize for re-posting - I have half a suspicion
that my original message did not make it through.
I hope you all had a good weekend and look forward to your reply,
MO
On Fri, Jul 20, 2012 at 11:56 AM, MO wrote:
> Dear R help list,
>
> I have done a lot of searching but have not been able to find an answer to
> my problem. I apologize in advance if this has been asked before.
>
> I am applying a mixed model to my data using lmer. I will use sample data
> to illustrate my question:
>
> >library(lme4)
> >library(arm)
> >data("HR", package = "SASmixed")
> > str(HR)
> 'data.frame': 120 obs. of 5 variables:
> $ Patient: Factor w/ 24 levels "201","202","203",..: 1 1 1 1 1 2 2 2 2 2
> ...
> $ Drug : Factor w/ 3 levels "a","b","p": 3 3 3 3 3 2 2 2 2 2 ...
> $ baseHR : num 92 92 92 92 92 54 54 54 54 54 ...
> $ HR : num 76 84 88 96 84 58 60 60 60 64 ...
> $ Time : num 0.0167 0.0833 0.25 0.5 1 ...
>
> > fm1 <- lmer(HR ~ baseHR + Time + Drug + (1 | Patient), HR)
>
> > fixef(fm1) ##Extract estimates of fixed effects
>
> (Intercept) baseHR Time Drugb Drugp
>
> 32.6037923 0.5881895 -7.0272873 4.6795262 -1.0027581
>
> > se.fixef(fm1) ##Extract standard error of estimates of fixed effects
>
> (Intercept) baseHR Time Drugb Drugp
>
> 9.9034008 0.1184529 1.4181457 3.5651679 3.5843026
>
> ##Because the estimate of the fixed effects are displayed as differences
> from the intercept (I think?), I can back calculate the actual effect sizes
> easily enough. However, how would I do a similar calculation for the
> standard error for these effect sizes (since these error estimates are for
> the difference in means of effects) if my design isn't balanced (which
> confuses things tremendously when working with a data set as large as
> mine)? It may help to point out that I'm working with microarray data;
> applying the same model for each gene (hundreds of genes total) across
> multiple samples (hundreds of samples total), but as an R beginner I like
> to start with small data samples and work my way up.
>
> I appreciate the help,
>
> MO
>
>
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