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Re: st: corr_svy & covariance matrix for survey data
Hi,
I wrote -corr_svy-, so here goes.
There are a couple of things going on here: (1) -corr_svy- is a version
7 command, and seems to be having some trouble interacting with the way
that Stata 10 stores the survey characteristics as set by -svyset-. (2)
-corr_svy- uses the older, more limited syntax for the -subpop()- option.
Issue (2) means that your subpop option must be specified as a single
variable name that takes on values 1 or 0 for cases that are in or out
of your subpopulation, respectively. If you have a complex condition,
you must first generate such a variable.
So, the following *should* work, but does not:
. sysuse auto
. svyset rep78 [pw=weight]
. corr_svy mpg price , subpop(foreign) sig
Survey Correlation
pweight: <none>
Strata: <one>
PSU: <observations>
Number of observations: 22
| mpg price
-------------+------------------------
mpg | 1.0000
|
|
price | -0.6313 1.0000
| 0.0042
--------------------------------------
Key: Estimated Correlation
Significance Level
As indicated in the output, -corr_svy- has ignored the survey
characteristics.
However, you can specify the survey characteristics in the -corr_svy-
command itself:
. corr_svy mpg price [pw=weight], psu(rep78) subpop(foreign) sig
Survey Correlation
pweight: weight
Strata: <one>
PSU: rep78
Number of observations: 21
| mpg price
-------------+------------------------
mpg | 1.0000
|
|
price | -0.5735 1.0000
| 0.0344
--------------------------------------
Key: Estimated Correlation
Significance Level
This gives you what you wanted.
(-corr_svy- will also set the survey characteristics you specify in a
way that subsequent calls to -corr_svy- can see, so you really only need
to specify them in the first run.)
What's going on? With version 9 Stata reworked completely the way that
survey characteristics are stored, presumably to support the
enhancements to the survey capabilities (such as supporting multiple
rounds of sampling). -corr_svy- uses the un/non-documented Stata
program -svy_get- to retrieve survey characteristics if they are not
specified in the command line. Unfortunately this is a Stata 8 command,
and cannot "see" the version 9+ survey characteristics.
In the long run I will fix -corr_svy- to deal with the new survey
characteristics. In the short run you can simply specify them when you
run -corr_svy_, or with a call to the version 8 -svyset-, like this:
. version 8: svyset ....
As a side effect, this means that -corr_svy- cannot deal with the more
complex sample specifications allowed with version 9+.
- Nick Winter
Ishtar Govia wrote:
Dear List,
I am using Stata 10/SE 10.1 for Macs. I have two questions. One
concerning the --corr_svy-- module and error messages I have been
getting, the second concerning how to obtain a covariance matrix for
complex survey sample data, within Stata.
I am working with a complex survey sample dataset and am using Stata for
some preliminary data analyses (univariate and multivariate checks for
normality, efas) before moving to Mplus for SEM modeling. I installed
the --corr_svy-- module from within Stata by typing "ssc install corr_svy"
However, in my first attempt below, I got the following error message:
svy, subpop (if race3cat==2 & sex==1 & (riwyes==1 & riwyes <.)):
corr_svy lesscurt lessresp poorserv notsmart actfraid thkdisho actbettr
callnmes trethara follstor, pw obs sig
corr_svy is not supported by svy with vce(linearized); see help svy
estimation for a list of Stata estimation commands that are supported by
svy
r(322);
I then attempted to reset the weight and design variables, and run the
--corr_svy--, following the example in the "help" for the --corr_svy--,
excluding my subpop specification.
. svyset clust [pweight=wgtcentriw], strata (stratum) ||_n
Note: stage 1 is sampled with replacement; all further stages will be
ignored
pweight: wgtcentriw
VCE: linearized
Single unit: missing
Strata 1: stratum
SU 1: clust
FPC 1: <zero>
. corr_svy lesscurt lessresp poorserv notsmart actfraid thkdisho
actbettr callnmes trethara follstor, pw obs sig
This worked--but it didn't include my subpop specification. I then tried
the same thing with my subpop specifcation and it DIDN'T work. Any ideas
on how to use the corr_svy module to obtain the correlation matrix,
accounting for the weight and design variables and allowing me to
restrict my analyses to my subpop of interest?
corr_svy lesscurt lessresp poorserv notsmart actfraid thkdisho actbettr
callnmes trethara follstor [pweight=wgtcent], strata(stratum) psu(clust)
subpop(if race3cat==2 & sex==1 & (riwyes==1 & riwyes <.)) pw obs sig
print(10) star(5)
subpop() does not contain a valid varname
r(198);
. svyset clust [pweight=wgtcentriw], strata (stratum) ||_n
Note: stage 1 is sampled with replacement; all further stages will be
ignored
pweight: wgtcentriw
VCE: linearized
Single unit: missing
Strata 1: stratum
SU 1: clust
FPC 1: <zero>
. corr_svy lesscurt lessresp poorserv notsmart actfraid thkdisho
actbettr callnmes trethara follstor, pw obs sig
In addition, does anyone know how to use the matrix I am trying to
obtain above to obtain a covariance matrix that can be easily
transferred to Mplus or LISREL for CFA and SEM analyses?
Thanks for your consideration,
Ishtar Govia
[email protected]
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--
--------------------------------------------------------------
Nicholas Winter 434.924.6994 t
Assistant Professor 434.924.3359 f
Department of Politics [email protected] e
University of Virginia faculty.virginia.edu/nwinter w
PO Box 400787, 100 Cabell Hall
Charlottesville, VA 22904
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/