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Antwort: st: RE: RE: graph for propensity scores


From   "Hans J. Baumgartner" <hbaumgartner@diw.de>
To   statalist@hsphsun2.harvard.edu
Subject   Antwort: st: RE: RE: graph for propensity scores
Date   Wed, 13 Apr 2005 10:53:52 +0200

That?s exactly the reason why propensity scores should be shown in the 
?upwards and downwards? design, since the graph shall show that both 
groups do have a common support area. 

I?ll check the reference anyway. 

Hans





++++++++++++++++++++++++++++++++
Hans J. Baumgartner
Dept. Public Economics
DIW Berlin
German Institut for Economic Research
phone: +49/30/89789-307
fax :      +49/30/89789-114
URL: www.diw.de
          www.hansbaumgartner.de
++++++++++++++++++++++++++++++++

owner-statalist@hsphsun2.harvard.edu wrote on 12/04/2005 15:57:22:

> Upwards and downwards designs appear popular 
> for no good reason. In effect the reader is 
> expected to be able to pick up one length, 
> transfer it and superimpose it, all in one's
> head, upon another length. Why this should be easier 
> or more effective than comparing juxtaposed lengths 
> beats me. 
> 
> The same issue arises with left and right 
> (side-by-side) designs such as population 
> pyramids. 
> 
> In each case, small and subtle differences 
> could easily be of interest or importance. 
> 
> The problem with histograms is naturally the 
> loss of detail produced by binning. Often 
> this is unimportant but frequently a researcher
> does want to be sure that is so. 
> 
> To compare two sets of values qua distributions, 
> -qqplot- is pretty nearly an optimal plot. To 
> compare them as paired values, there are several 
> good methods. A fairly lengthy discussion with 
> references is given in 
> 
> Graphing agreement and disagreement. 
> Stata Journal 4(3): 329--349 (2004)
> 
> Nick 
> n.j.cox@durham.ac.uk 
> 
> David Harrison
> 
> > You could do that something like, e.g.
> > 
> > sysuse auto
> > twoway__histogram_gen length if !foreign, start(140) w(10) 
> > freq gen(h0 x0)
> > twoway__histogram_gen length if foreign, start(140) w(10) 
> > freq gen(h1 x1)
> > replace h1=-h1
> > gen zero=0
> > twoway (rbar h0 zero x0, barw(10)) (rbar h1 zero x1, barw(10)), ///
> >     yla(-10 "10" -5 "5" 0(5)15) yti(Frequency) ///
> >     legend(label(1 "Domestic") label(2 "Foreign"))
> > 
> > Note the very handy command -twoway__histogram_gen- (two 
> > underscores in the first gap!) that is not in the Stata 
> > manuals but does have a help file.
> 
> Hans J. Baumgartner
> 
> > I am estimating treatment effects using propensity scores.
> > 
> > To discuss the common support I?d like to graph the scores for the 
> > treated and the controls.
> > 
> > However, my graph knowledge is very limited and is only sufficient to 
> > generate a graph, where the scores for the treated and the 
> > controls are 
> > displayed next to each other. That is I am using the by(.) option and 
> > the command historgram.
> > 
> > I?ve seen the scores are displayed upwards for the treated 
> > and mirrored 
> > downwards for the controls in one single graph.
> > 
> 
> *
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> 


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