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Re: st: using -mixed- with clustered data that includes probability weights


From   Stas Kolenikov <[email protected]>
To   "[email protected]" <[email protected]>
Subject   Re: st: using -mixed- with clustered data that includes probability weights
Date   Thu, 27 Feb 2014 20:21:19 -0500

Whether your results are biased really depends on your study design.
-mixed- knows nothing about your design (Stata 14 request: a command
to read the pdf file and extract the design information from the
narrative -- may I suggest -pdf2svyset- as a prospective name? I am
sure a lot of researchers would find this handy), and just warns you
in case you had sampling at several levels. If there were no sampling
at the doctor's level, then weighting only at the patient level that
you have is appropriate.

-- Stas Kolenikov, PhD, PStat (ASA, SSC)
-- Principal Survey Scientist, Abt SRBI
-- Opinions stated in this email are mine only, and do not reflect the
position of my employer
-- http://stas.kolenikov.name



On Thu, Feb 27, 2014 at 7:55 PM, Stephen Henry <[email protected]> wrote:
> Hi,
>
> I want to know whether I can used -mixed- in Stata 13.1 to analyze
> clustered data that include probability weights.
>
> My data were collected to study patients during clinic visits.
> Each patient is unique, and patients are clustered within doctors.
> In addition, patients were sampled based on an illness severity score.
> Patients with more severe symptoms were over-sampled.
> Patient sampling was done independent of which doctor was seeing the
> patient.
>
> I have been analyzing data using the -reg- command and cluster option as
> follows:
>
> reg v1 v2 v3 [pweight=weight], cluster(doctor_id)
>
> However, I'd like to use -mixed- instead to take advantage of the
> additional postestimation commands.
>
> Stata will run the following command:
>
>  mixed v1 v2 v3 [pweight=weight] || doctor_id:
>
> but warns me that "Sampling weights were specified only at the first level
> in a multilevel model."
> Are my results with the -mixed- command potentially biased?  If so, is
> there an easy way to fix this?
>
> Thanks in advance,
>
> Stephen Henry
> University of California Davis
> Sacramento, California
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