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Re: st: Scatter with regression line and confidence interval densities


From   "Steichen" <[email protected]>
To   <[email protected]>
Subject   Re: st: Scatter with regression line and confidence interval densities
Date   Sat, 17 Jul 2004 08:33:09 -0400

Fredrik -

I just tried it and it ran without error on Stata 8.2 on an XP PC.

Did you cut-and-paste Vince's code into the do file editor or did you retype
and introduce a subtle error?  You might tell us where the error occurred
(though I suspect in the -twoway- code).

Tom

----- Original Message ----- 
From: "Fredrik Wallenberg" <[email protected]>
To: <[email protected]>
Sent: Saturday, July 17, 2004 3:05 AM
Subject: Re: st: Scatter with regression line and confidence interval
densities


> I tried to run Vince's code (just to see what it would look like) and I
get
>
> option not allowed
> invalid syntax
>
> I am running an up-to-date copy of Intercooled Stata 8 (mac).
>
> Fredrik
>
> On Fri, 16 Jul 2004 09:06:15 -0500, Vince Wiggins, StataCorp
> <[email protected]> wrote:
> > Scott Merryman <[email protected]> wrote,
> >
> > > In the June 2004 issue of the American Economic Review, the back
> > > cover has an ad from Stata emphasizing the graphics of Stata 8.  One
> > > of the graphs shows a scatter plot with a regression line and
> > > confidence interval densities.  It looks something like the graph on
> > > page 2 of
> > >
> > > http://www.asft.ttu.edu/ansc5403/lecture25.pdf
> > >
> > > How does one include the confidence densities in a regression line
graph?
> >
> > This graph superimposes vertical density line plots for the distribution
of
> > the disturbances on a regression line.  Such graphs are sometimes seen
in
> > textbooks when trying to provide intuition for linear regression.  For
data
> > analysis, the confidence intervals shown by -twoway lfitci y x- are
easier to
> > read, but the graph from the ad has its own appeal.  Here is the code
used to
> > produce that graph,
> >
> > ---------------------------------- BEGIN --- regline_ci.do --- CUT
HERE -------
> > clear
> > sysuse auto
> > keep if foreign
> > sort weight
> >
> > gen weight2 = weight^2
> > regress mpg weight weight2
> > predict fit
> > predict se , stdp
> >
> > #delimit ;
> > twoway sc mpg weight , pstyle(p3) ms(o)
||
> >        fn weight[3]  - 1000 * normden(x, `=fit[3]' , `=se[3]') ,
> >                 range(`=fit[3] -5' `=fit[3] +5') horiz pstyle(p1)
||
> >        fn `=fit[3]' , range(`=weight[3]' `=weight[3]-1000*normden(0,
se[3])')
> >                       pstyle(p1)
||
> >        fn weight[17] - 1000 * normden(x, `=fit[17]', `=se[17]') ,
> >                 range(`=fit[17]-5' `=fit[17]+5') horiz pstyle(p1)
||
> >        fn `=fit[17]', range(`=weight[17]' `=weight[17]-1000*normden(0,
se[17])')
> >                       pstyle(p1)
||
> >        fn weight[21] - 1000 * normden(x, `=fit[21]' , `=se[21]') ,
> >                 range(`=fit[21] -7' `=fit[21] +7') horiz pstyle(p1)
||
> >        fn `=fit[21]', range(`=weight[21]' `=weight[21]-1000*normden(0,
se[21])')
> >                       pstyle(p1)
||
> >        line fit weight
> >         , clwidth(*2) legend(off) ytitle(Miles per gallon)
xtitle(Weight)
> >           title("Scatter with Regression Line and Confidence Interval
Densities"
> >           , size(4.8) margin(t=0 b=1.5) span)
> > ;
> > #delimit cr
> > ----------------------------------   END --- regline_ci.do --- CUT
HERE -------
> >
> > The graph is cute in that the CI densities are not notional, but rather
the
> > actual CIs from our regression of -mpg- on -weight- and -weight-
squared.  We
> > have pulled the SE estimates from the regression fit, SEs obtained with
> > -predict se , stdp-, at observations 3, 17, and 21 and supplied those to
the
> > -fn- (or -function-) plots using the -normden()- function to get our CI
lines
> > (we cheated ever so slightly and did not use a t-distribution).  Note
that we
> > scale the result of -normden()- by 1000 so that it looks about right on
the
> > scale of the weight axis -- a scale that runs from 1,500 to 3,500.  We
need to
> > do this because the X-axis is not scaled as a density.  Our choice of
1000 as
> > the scaling is arbitrary -- we can only compare the relative heights of
the CI
> > densities on this graph.  We also took some care to get an appropriate
range
> > in the -mpg- dimension for each of our CI densities.
> >
> > The other three -fn- plots just draw the drop lines from the top of the
CI
> > densities to the regression line.
> >
> > -- Vince
> >    [email protected]
> >
> >
> >
> > *
> > *   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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