Where do I get the -perturb- command from?
----- Original Message -----
From: "John Hendrickx" <[email protected]>
To: <[email protected]>
Sent: Thursday, January 15, 2004 10:50 AM
Subject: RE: st: Re: collinearity and xtprobit, xtlogit
> Unzip the files in your personal ado directory (e.g. c:\ado\personal)
> and run the perturb command, e.g.
>
> global ptrans1 "exp2=exp^2"
> *set trace on
> #delimit ;
> perturb: xi3: reg ses fses*eyr educyr*eyr fses*exp educyr*exp exp2,
> poptions(pvars(eyr exp) prange(5 5) niter(10)) beta;
> #delimit cr
>
> Use -help perturb- for further information.
>
>
> --- "Lin, Chung-Tung" <[email protected]> wrote:
> > That's great. Which of the 4 files does this? Thank you.
> >
> > Jordan Lin
> > Consumer Studies Team
> > Food and Drug Administration
> > 5100 Paint Branch Parkway, HFS-727
> > College Park, MD 20740
> > (Tel) 301-436-1831
> >
> > -----Original Message-----
> > From: John Hendrickx [mailto:[email protected]]
> > Sent: Wednesday, January 14, 2004 11:14 AM
> > To: [email protected]
> > Subject: Re: st: Re: collinearity and xtprobit, xtlogit
> >
> > As noted in the thread referred to here, collinearity is a problem
> > among the independent variables. An often used approach is to run a
> > regression with any dependent variable and then run the
> > collinearity
> > diagnostics.
> >
> > I proposed an alternative approach in my posting to that thread.
> > Collinearity is a problem if independent variables are so strongly
> > correlated that estimates become unstable, i.e. if a small change
> > to
> > one of the independent variables causes strongly different
> > parameter
> > estimates. I've written an ado-program that will do this for you.
> > It
> > estimates your model 100 times, adding a random value to specified
> > variables at each iteration. It's not limited to regression models
> > and it can handle interactions, transformed variables, and
> > categorical variables.
> >
> > A priliminary version is available at
> > http://www.xs4all.nl/~jhckx/stata/perturb/
> > Take a look and let me know what you think.
> >
> > John Hendrickx
> >
> > --- john emmet <[email protected]> wrote:
> > > Dear Scott,
> > > Thanks very much for replying.
> > >
> > > I'm sorry, I must not have explained myself very clearly in my
> > > original
> > > posting.
> > >
> > > I did mention, though that if I were using a cross-sectional
> > > dataset I
> > > would probably use -collin- but as I am not I can't. The
> > dataset
> > > is a
> > > panel set with 6 panels and I am using xtprobit (but could
> > consider
> > > xtlogit)
> > >
> > > I suppose I am trying to evaluate the situation relating to
> > > multicollinearity with time series cross-sectional analysis.
> > >
> > > Any help or advice from will be very gratefully received.
> > >
> > > John
> > >
> > > > One possibility would to be to use -collin-
> > > >
> > > > I would also suggest you take a look at the thread started by
> > > Matt Barreto
> > > > on
> > > > December 10th, 2003 ("multicollinearity test for probit?"), and
> > > the
> > > > replies by
> > > > Richard Williams, Nick Cox, Joao Pedro W. de Azevedo, and John
> > > Hendrickx.
> > > >
> > > > Scott
> > > >
> > > > ----- Original Message -----
> > > > From: "john emmet" <[email protected]>
> > > > To: <[email protected]>
> > > > Sent: Monday, January 12, 2004 10:04 AM
> > > > Subject: st: collinearity and xtprobit, xtlogit
> > > >
> > > >
> > > >> Hi
> > > >>
> > > >> I am new to panel data analysis, and I don't seem to be able
> > to
> > > forget
> > > >> my
> > > >> experience when using cross-sectional analysis in terms of
> > > avoiding
> > > >> multicollinearity amongst explanatory variables. All the
> > > analysis is
> > > >> using binary dependent variables.
> > > >>
> > > >> If I were doing logit I would probably use the collin command
> > > and
> > > >> examine
> > > >> the VIF, tolerance, etc.
> > > >>
> > > >> If I look at the correlation coefficients for the panel
> > dataset
> > > (6
> > > >> panels)
> > > >> they are very high for some explanatory variables, but then.
> > > But there
> > > >> is obviously some collinearity between the RHS variables
> > because
> > > when I
> > > >> put one variable in particular in the model, it affects the
> > prob
> > > values,
> > > >> SEs and coefficients.
> > > >>
> > > >> Am I completely missing a point somewhere????
> > > >>
> > > >> Is there a test for using with xt models?
> > > >>
> > > >> *
> > > >> * For searches and help try:
> > > >> * http://www.stata.com/support/faqs/res/findit.html
> > > >> * http://www.stata.com/support/statalist/faq
> > > >> * http://www.ats.ucla.edu/stat/stata/
> > > >
> > > > *
> > > > * For searches and help try:
> > > > * http://www.stata.com/support/faqs/res/findit.html
> > > > * http://www.stata.com/support/statalist/faq
> > > > * http://www.ats.ucla.edu/stat/stata/
> > > >
> > >
> > > *
> > > * For searches and help try:
> > > * http://www.stata.com/support/faqs/res/findit.html
> > > * http://www.stata.com/support/statalist/faq
> > > * http://www.ats.ucla.edu/stat/stata/
> >
> >
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>
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