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RE: st: AW: confidence intervals, saved results, pweights
From
"Martin Weiss" <[email protected]>
To
<[email protected]>
Subject
RE: st: AW: confidence intervals, saved results, pweights
Date
Sat, 17 Jul 2010 19:05:30 +0200
<>
For the "manual" approach, also see Maarten`s
http://www.stata-journal.com/article.html?article=st0137
HTH
Martin
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Steve Samuels
Sent: Samstag, 17. Juli 2010 18:49
To: [email protected]
Subject: Re: st: AW: confidence intervals, saved results, pweights
That's true of matrices e(b) and e(V) which are returned by every
Stata estimation command, not just -svy- commands. It's irritating.
You can:
matrix list e(V)
matrix v = e(V)
di el(v,1,1)
As to your first question, -parmest- is the best choice, as Martin
pointed out, but you can do it from first principles. You also don't
need to refer to the matrices, because Stata builds in _b[] and _se[]
system variables. See the -help- for "system variables".
*******************
sysuse auto, clear
svyset _n
svy: mean weight trunk
matrix v =e(V)
matrix list e(V)
di sqrt(el(v,1,1))
di _se[weight]
local bound_wt = _se[weight]*invttail(e(df_r),.025)
gen llim_wt = _b[weight]-`bound_wt'
gen ulim_wt = _b[weight]+`bound_wt'
di llim " " ulim
*********************
On Sat, Jul 17, 2010 at 11:29 AM, Martin Weiss <[email protected]> wrote:
>
> <>
>
> Try Roger`s -ssc d parmest-:
>
>
> *************
> capture which parmest
> if _rc ssc install parmest
>
> webuse fpc, clear
> svyset [pw=weight]
> svy: mean x
> parmest, saving(myfile, replace)
>
> u myfile, clear
> l
> *************
>
>
>
> HTH
> Martin
>
>
> -----Ursprüngliche Nachricht-----
> Von: [email protected]
> [mailto:[email protected]] Im Auftrag von Ben Zipperer
> Gesendet: Samstag, 17. Juli 2010 17:24
> An: [email protected]
> Betreff: st: confidence intervals, saved results, pweights
>
> confidence intervals of variable means in survey data with pweights.
>
> As I understand it, -svy: mean- will show the confidence interval, but
> only returns the variance and mean in its e() results. Is it
> recommended that I simply use these e() results to calculate my own
> confidence interval (to match the one reported but not saved by -svy:
> mean-), or is there a command like -ci- that saves as macros the
> confidence interval results with pweighted survey data?
>
> Additionally, after -svy: mean- why can I display the elements of some
> variance matrices but not others? For example,
>
> . webuse fpc, clear
>
> . svyset [pw=weight]
>
> pweight: weight
> VCE: linearized
> Single unit: missing
> Strata 1: <one>
> SU 1: <observations>
> FPC 1: <zero>
>
> . svy: mean x
> (running mean on estimation sample)
>
> Survey: Mean estimation
>
> Number of strata = 1 Number of obs = 8
> Number of PSUs = 8 Population size = 27
> Design df = 7
>
> --------------------------------------------------------------
> | Linearized
> | Mean Std. Err. [95% Conf. Interval]
> -------------+------------------------------------------------
> x | 5.448148 .723725 3.73681 7.159486
> --------------------------------------------------------------
>
> . di el(e(V_srs),1,1)
> .54734078
>
> . di el(e(V),1,1)
> matrix operators that return matrices not allowed in this context
>
> thanks,
> Ben
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>
>
> *
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>
--
Steven Samuels
[email protected]
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax: 206-202-4783
*
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