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Re: st: how to do fixed effects with weights? (problem using svy: with xtreg, fe)
From
Steve Samuels <[email protected]>
To
[email protected]
Subject
Re: st: how to do fixed effects with weights? (problem using svy: with xtreg, fe)
Date
Sun, 11 Apr 2010 21:46:19 -0400
Because -xtreg- accepts probability weights, you do not need Stata's
-svy- utilities. Create a -forvalues- loop to run the -xtreg- command
91 times, once with the original weights and once with each replicate
weight. Save the estimates of interest (they will be in system
variables _b[incneed] _b[married] etc. and other returned results)
with -postfile- and then do the jackknife calculations "by hand". You
can also jackknife the covariance matrix of the estimates and do tests
of the significance of groups of the predictors and interactions. In
addition to any graphical tests of fit you can think of, you can do a
jackknifed version of Stata's -linktest- or similar tests. Note that
the likelihood based measures of fit like BIC are not available for
survey data.
Good luck
Steve
On Sun, Apr 11, 2010 at 3:43 PM, <[email protected]> wrote:
> I am analyzing longitudinal data on children's educational achievement using
> the "xtreg, fe" command. My challenge is that I can't seem to weight the
> data with the "svy:" command when running a fixed effects model. I am
> working with Early Childhood Longitudinal Study-Kindergarten Cohort data
> from the National Center for Education Statistics; the study employed a
> multistage probability sample design (with three stages).
>
> As advised by a technical consultant at the American Institutes for
> Reserach, I am currently "survey setting" the data using replicate weights
> as follows:
> svyset [pweight=c1_5fp0], jkrweight( c1_5fp1-c1_5fp90, multiplier(1))
>
> I then attempted to run the fixed effects model with this syntax:
> svy jacknife: xtreg ztime incneed married momwork numchild, i(childid2) fe
>
--
Steven Samuels
[email protected]
18 Cantine's Island
Saugerties NY 12477
USA
Voice: 845-246-0774
Fax: 206-202-4783
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