[R] Subpopulations in Complex Surveys

[Thompson, Trevor]

For svymean, can't you just pass the subpopulation into the design argument?

> svymean(~crc10yr, design=nhis.design[nhis.design$variables$age>=50,],
na.rm=TRUE)
  crc10yr 
0.3461349 
attr(,"var")
             [,1]
[1,] 2.903020e-05
> svyglm(crc10yr~I(age>=50)+0, design=nhis.design)
Stratified 1 - level Cluster Sampling design
With ( 678 ) clusters.

Call:  svyglm(formula = crc10yr ~ I(age >= 50) + 0, design = nhis.design) 

Coefficients:
I(age >= 50)FALSE   I(age >= 50)TRUE  
           0.1109             0.3461  

Degrees of Freedom: 17802 Total (i.e. Null);  17800 Residual
Null Deviance:      0.1394 
Residual Deviance: 0.09631      AIC: 6.601 

-trevor

-----Original Message-----
From: Thomas Lumley [mailto:tlumley at u.washington.edu]
Sent: Sunday, February 23, 2003 1:17 PM
To: TyagiAnupam at aol.com
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] Subpopulations in Complex Surveys


On Wed, 19 Feb 2003 TyagiAnupam at aol.com wrote:

> Hi,
> is there a way to analyze subpopulations (e.g. women over 50, those who
> answered "yes" to a particular question) in a survey using Survey package?
> Other packages (e.g. Stata, SUDAAN) do this with a subpopulation option to
> identify the subpopulation for which the analysis shoud be done. I did not
> see this option in the Survey package. Is there another way to do this?
>

Not directly.

This only really matters for svymean. For the regression models it's just
a convenience as you can specify a model that has an interaction with the
subpopulation indicator to get estimates and standard errors in the
subpopulation.

For svymean you can use a regression model too:
Instead of a hypothetical   svymean(~x, design=d, subpop=race==2)  do
   svyglm(x~I(race==2)+0, design=d)

I need to work out if there's a general way to handle subpopulations or
whether it needs to be coded on a case by case basis.


	-thomas

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