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Re: st: RE: Graphing multiple cdf's in the same graph (using either -distplot- or -cdfplot-)


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Graphing multiple cdf's in the same graph (using either -distplot- or -cdfplot-)
Date   Tue, 5 Mar 2013 19:50:35 +0000

-distplot- (SJ) can be used with such data as follows

preserve

label define vars 1 "var1" 2 "var2"
stack var1 var2, into(vars) clear
drop if missing(vars)
label val _stack vars
distplot vars, over(_stack)
...
restore

On Tue, Mar 5, 2013 at 10:43 AM, Nick Cox <njcoxstata@gmail.com> wrote:
> Thanks to David for the explanation. However, although -distplot- is
> available from SSC, it
> was first published in the STB and subsequent updates have continued
> in the Stata Journal.

<snip>

> All that said, no version of -distplot- supports what Max wants, given
> its treatment of missing values and as David and Maarten have
> explained you need to do that otherwise.
>
> Nick
>
> On Mon, Mar 4, 2013 at 10:26 PM, David Radwin <dradwin@mprinc.com> wrote:
>
>> Please remember to cite sources for user-written programs. -distplot- is
>> by Nick Cox and -cdfplot- is by Adrian Mander. Both are available from
>> SSC.
>>
>> You can create your own CDFs using -cumul- and then plot them using
>> -twoway line-. The following example is based on this message by Nick Cox:
>> http://www.stata.com/statalist/archive/2005-04/msg00800.html
>>
>> sysuse nlsw88, clear
>> gen wageodd=wage if mod(_n,2)==1 // odd-numbered observations
>> gen wageeven=wage if mod(_n,2)==0 // even-numbered observations
>>
>> kdensity wageodd, gen(a b)
>> cumul b, gen(cb)
>>
>> kdensity wageeven, g(c d)
>> cumul d, gen(cd)
>>
>> twoway (line cb b, sort ) (line cd d, sort lpattern(dash))
>
> Max.Livingston
>
>>> I'm trying to plot two cdf's on the same axis. -distplot- allows me to
>> do
>>> this (simple example: distplot line var1 var2, lc(red blue)  ) , but
>>> there's a wrinkle in my data that makes this more complicated. The data
>> is
>>> arranged such that var1 and var2 are never both non-missing. That is,
>> for
>>> every observation where var1 exists, var2 is missing, and vice versa. I
>> am
>>> able to graph this using kernel density:
>>> twoway (kdensity var1, lp(solid) lc(blue))
>>>  || (kdensity var2, lp(solid) lc(red))
>>>
>>> But I can't seem to find a similar implementation for -distplot- (or
>>> -cdfplot- for that matter). If anyone has any ideas, I would greatly
>>> appreciate it.
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