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Re: st: sample survey analysis without PSU info


From   Steven Samuels <ssamuels@albany.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: sample survey analysis without PSU info
Date   Thu, 12 Mar 2009 18:41:53 -0400

Carlos, with only stratum information and weights, you cannot estimate standard errors. Correct standard errors depend mostly on the number of PSU's and on the variation between them. Any standard errors that ignore the design will be completely useless. Almost always they will be lower than the real standard errors and they could be much lower.

However many surveys that do not identify PSU's supply other means of computing standard errors. For example, they may identify replicates to use with replicated-based variance methods. Or, the documentation may contain formulas or design effects for approximating the standard errors. Without such additional information, you have _no_ remedy.


A good reference is Sharon Lohr's book Sampling: Design and Analysis, Duxbury, 1999.

Steve

If not, there is no remedy.
On Mar 12, 2009, at 11:42 AM, Carlos Dias wrote:

Dear Statalisters,
I am preparing to analyse a large sample survey data file (about 40000
individuals where all individuals in families are surveyed). This
comes from a multistage, cluster sample survey where strata=regions,
PSU=counties, and sample weights calculated using Horwitz-Thompson
methods in R and then post-stratification with marginal adjustements
for age and sex.

I have sample weights and strata information for each individual but
no information on the PSU (counties within strata) of each individual.

Could someone direct me to references on the risks and ways to
minimize them when I conduct the analysis without cluster information
on the svyset command?

Thank in advance

Carlos Dias
National School of Public Health, New University of Lisbon
Lisbon, Portugal
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