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Re: st: graphing estimates and confidence intervals


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: graphing estimates and confidence intervals
Date   Sun, 12 May 2013 13:16:41 +0100

Excellent point.

On 10/05/2013, Alan Neustadtl <alan.neustadtl@gmail.com> wrote:
> As usual, Nick Cox's canonical replies are tremendously useful to both
> teach and remind us of how to approach a number of Stata problems.  Thank
> you for your comments.
>
> I add another approach using -marginsplot- as in the following example:
>
> sysuse auto
> regress mpg i.for
> margins i.for
> marginsplot, recast(scatter)
>
> Best,
> Alan
>
> On Fri, May 10, 2013 at 8:52 AM, Nick Cox <njcoxstata@gmail.com> wrote:
>> Two recent threads both centred on graphical display of estimates
>> together with confidence intervals: The start points were
>>
>> http://www.stata.com/statalist/archive/2013-05/msg00293.html
>>
>> http://www.stata.com/statalist/archive/2013-05/msg00310.html
>>
>> This post is intended mainly as a kind of broad-brush overview of the
>> question. It also adds some detail omitted from those threads. In
>> turn, naturally, please comment if I miss anything of importance or
>> interest.
>>
>> The main idea is that while estimates can be plotted easily with
>> -twoway scatter- or -graph dot- you are in practice going to find it
>> difficult to show confidence intervals directly other than by -twoway
>> rcap-. (It's only convention that might inhibit you from using -twoway
>> rspike- instead.) It follows that you need to focus on using -twoway-.
>> Bluntly, -graph dot- (or -graph bar- for those so inclined) is a dead
>> end here.
>>
>> There are two broad strategies.
>>
>> 1. You can build your own command by assembling a composite -twoway-
>> call using -scatter- for the point estimates and -rcap- for the
>> intervals. This can be combined, with increasing difficulty, with
>> showing different results for different groups on one or more levels.
>> An example to explain levels here: using sex as a classifier gives one
>> level and using race or region or both would add one or two more
>> levels.
>>
>> With one level you will presumably just want to plot your grouping
>> variable on one of the axes.
>>
>> With two or more levels, using -by()- is the easiest approach to add
>> an extra level of classification, but just adding spacing can be as or
>> more effective. Sometimes with -by()- there is too much scaffolding
>> and too much loss of real estate.
>>
>> If you have any group variable that is string, things are easier if
>> you -encode- it or use -egen, group()- to produce an equivalent
>> numeric variable with value labels.
>>
>> 2. Alternatively, you can look for a command that does all that for
>> you. The commands differ in whether they expect that you already have
>> the estimates (point and interval) or they will undertake to do that
>> calculation for you. The more standard the calculation, the more
>> likely that a canned command already exists.
>>
>> -serrbar- is an old official command which doesn't do much but may
>> match simple needs. My impression is that it is little known, but that
>> may be because it is little mentioned, and that in turn because it is
>> of little use.
>>
>> -dotplot- is an official command which supports display of mean +/-
>> SD. It's worth knowing that, but it's unlikely to be what you want
>> under this heading.
>>
>> -ciplot- is an oldish user-written command (SSC, Nick Cox). Its basic
>> idea is to call up -ci- repeatedly and then plot the results. There is
>> support for multiple groups and multiple variables. If it doesn't go
>> as far as you want, the bad news is that I have no interest in
>> developing it, but it's more flexible than any official command I can
>> recall. For example,
>>
>> sysuse auto
>> ciplot foreign , binomial jeffreys by(rep78)
>>
>> shows how you can reach through to -ci-.
>>
>> -stripplot- (SSC, Nick Cox) was mentioned in recent posts. Its display
>> of confidence intervals is based on exactly the same idea as -ciplot-,
>> to call up -ci- for the calculations. Its philosophy is to show the
>> raw data too, although nothing beyond an ectoplasmic sense of my mild
>> disapproval stops you suppressing the data display with e.g
>> -ms(none)-.
>>
>> -eclplot- (SSC also SJ, Roger Newson) is another user-written command,
>> and one characteristically well thought out, documented and
>> maintained. It's not competing because it is focused on a different
>> case, in which you already have estimates and confidence limits to
>> hand; other programs of Roger's are of much help in assembling and
>> analysing such results.
>>
>> I want to flag strongly the scope for using -statsby- in this
>> territory, which I wrote up in
>>
>> SJ-10-1 gr0045  . . . . . . . . . . . . . Speaking Stata: The statsby
>> strategy
>>         . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  N. J.
>> Cox
>>         Q1/10   SJ 10(1):143--151                                (no
>> commands)
>>         demonstrates the use of statsby to prepare a reduced
>>         dataset for subsequent graphing
>>
>> .pdf freely available at
>> http://www.stata-journal.com/sjpdf.html?articlenum=gr0045
>>
>> Confidence intervals are a major example. (That paper was inspired by
>> a single throw-away remark by Vince Wiggins. It was one of many
>> occasions in which deciding to write about something made me aware of
>> something in Stata I was underestimating.)
>>
>> I would also like to mention a general discussion of graphical technique
>> in
>>
>> SJ-8-2  gr0034  . . . . . . . . . .  Speaking Stata: Between tables and
>> graphs
>>         (help labmask, seqvar if installed) . . . . . . . . . . . .  N. J.
>> Cox
>>         Q2/08   SJ 8(2):269--289
>>         outlines techniques for producing table-like graphs
>>
>> .pdf freely available at
>> http://www.stata-journal.com/sjpdf.html?articlenum=gr0034
>>
>> Nick
>> njcoxstata@gmail.com
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-- 
Nick
njcoxstata@gmail.com
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