Rolf,
I actually don't believe that this is a SAS vs R issue since I have 3
sources that report the same results. I know that STATA, SAS and the
mima function from R can all be used to give the correct results. The
question is related more to how I can get similar results with lmer.
Currently, the code I provided generates VERY different results,
especially related to between study variance estimation (tau) and
regression coefficient standard errors. Basically, I think I got it
all wrong in my coding of the models with covariates (f3 and f4), but
I can't understand why.
Brant
On May 5, 2009, at 11:43 PM, Rolf Turner wrote:
On 6/05/2009, at 3:00 PM, Brant Inman wrote:
R-experts:
In 2002, Hans Van Houwelingen et al. published a tutorial on how to
do
meta-regression in Statistics in Medicine. They used the classic BCG
dataset of Colditz to demonstrate correct methodology and computed
the
results using PROC MIXED in SAS. In trying to duplicate the results
presented in this paper, I have discovered that I can reproduce
certain items with lmer but not others. I was hoping that someone
might point out how I could correctly program R code to arrive at the
correct solution.
<snip>
There appears to be a tacit assertion here that the results from PROC
MIXED in The-Package-That-Must-Not-Be-Named are the correct results.
This assertion is very likely to bring the wrath of Doug Bates down
upon your head. An outcome to be devoutly avoided! :-)
cheers,
Rolf Turner
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