[R] large survey data set

[rpietro@duke.edu]

Thanks for the reply. By "handle" i mean to adjust the standard errors so
that i can draw inferences about the target population. In my case, my
data set represents a 20% of the US population, and adjusting for the
weights my confidence intervals are corrected for the US population rather
than the local data set.

On Thu, 27 Jun 2002, Andrew Perrin wrote:

> Data management isn't all that easy in R, but it's certainly
> possible.  There are some good tips here:
> http://cran.r-project.org/doc/contrib/usingR.pdf
>
> You can also put the data in a database and access them with one of the
> database interfaces available (RODBC, RMySQL, RPgSQL).
>
> I'm not sure what you mean by "handle" weights, clusters, and
> strata. I'm guessing you want to use the nlme package, but it really
> depends on what questions you want to ask.
>
> Best,
> Andy Perrin
>
> ----------------------------------------------------------------------
> Andrew J Perrin - http://www.unc.edu/~aperrin
> Assistant Professor of Sociology, U of North Carolina, Chapel Hill
> clists at perrin.socsci.unc.edu * andrew_perrin (at) unc.edu
>
>
> On Thu, 27 Jun 2002 rpietro at duke.edu wrote:
>
> >
> >
> > ---------- Forwarded message ----------
> > Hello,
> >
> >
> > I am analyzing a weighted, stratified, clustered survey data set
> > with approximately 1 million observations and 50 variables.
> >
> > I am new to R (I'm a Stata user), and so far
> > couldn't find any documentation on how to handle survey data. In
> > other words, is there a specific package to handle a combination of
> > weigths, clusters and strata. I am also struggling to
> > handle such a large data set. Any suggestions and/or references regarding
> > these two issues would be greatly appreciated.
> >
> >
> > Rick
> >
> >
> >
> >
> > Ricardo Pietrobon, MD
> > Assistant Professor of Surgery
> > Duke University Medical Center
> >
> >
> >
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>
>

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