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RE: st: tuples, stepwise and counting types of variables


From   Kieran McCaul <kieran.mccaul@uwa.edu.au>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: tuples, stepwise and counting types of variables
Date   Tue, 14 Aug 2012 09:46:02 +0800

...

The final model should leave its results in the matrix e(b) and you can get the variable names from this.
For example,

sysuse auto, clear
regress weight length turn displacement
local names : colfullnames e(b)
di "`names'"





-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Thomas Sohnesen
Sent: Tuesday, 14 August 2012 9:33 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: tuples, stepwise and counting types of variables

Thanks Nick

My question is how do i generate the "used" list after using stepwise
regression?  Stepwise (or another automated variable selection method)
decides which variables stay in the model.  I've counted the number of
variables in e(df_m), but i believe i need to save the actual names of
the variables that stay in the regression to use your suggested
approach.

thanks again
Thomas
On Mon, Aug 13, 2012 at 8:36 PM, Nick Cox <njcoxstata@gmail.com> wrote:
> I can't comment on analogues to MAXR as I am not familiar with SAS.
>
> For counting how many of a list are in another list, you can find the
> intersection of two lists using
>
> : list a & b
>
> as documented at -help macrolists-. and then count them.
>
> For example,
>
> local availablex "x1 x2 x3"
> local usedx "x2"
> local inter : list availablex & usedx
> di `: word count `inter'
>
> Nick
>
> On Tue, Aug 14, 2012 at 1:24 AM, Thomas Sohnesen <sohnesen@gmail.com> wrote:
>> Thanks Nick
>>
>> For this exercise i'm not interested in the coeffiicents or their
>> meaning, i'm looking to find a parsimonouce model for predictions.
>> Any advice on a better alternative than stepwise?  Doing it manually
>> is not really an option as we will be running a lot of different
>> models. Further, though my data is organized in blocks i would like to
>> keep single variables if they are highly correlated with my dependent
>> variable. I believe SAS has an alernative in MAXR. Do you know if
>> stata has a similar alternativ?
>>
>> Finally, no matter which alternativ we end up using, i still have the
>> challange of counting number of variables from each block in the final
>> model. Any insights on that?
>>
>> thanks and best
>>
>> Thomas
>>
>>
>> On Mon, Aug 13, 2012 at 5:30 PM, Nick Cox <njcoxstata@gmail.com> wrote:
>>> I belong to a club which is dedicated to advising people against using
>>> -stepwise-. A -search- will find an FAQ on this question.
>>>
>>> I'd look at -nestreg- instead.
>>>
>>> Nick
>>>
>>> On Mon, Aug 13, 2012 at 10:18 PM, Thomas Sohnesen <sohnesen@gmail.com> wrote:
>>>
>>>> I have a number of "groups" of variables as examplified below.
>>>>
>>>>
>>>> local gr1  x1 x2 x3 x4
>>>>
>>>> local gr2  x5 x6 x7 x8
>>>>
>>>> local gr3  x9 x10 x11 x12 x13 x14 x15
>>>>
>>>> local gr4    x16 x17
>>>>
>>>>
>>>>
>>>> I run stepwise regressions for all the combinations of these groups
>>>> using tuples.
>>>>
>>>> tuples "`gr1'" "`gr2'" "`gr3'" "`gr4'" , display
>>>>
>>>>                 forval i = 1/`ntuples' {
>>>>
>>>>  qui stepwise, pr(0.05):  regress y `tuple`i''
>>>>
>>>> }
>>>>
>>>>
>>>>
>>>> Now i would like to count how many variables from each group that
>>>> stayed in the step wise model.
>>>>
>>>>
>>>>
>>>> For instance in the stepwise regression of gr1 and gr2  (ei x1 x2 x3
>>>> x4   x5 x6 x7 x8) only x3 x4   x5 was included in the regression.  I
>>>> would then like an output along the lines of:
>>>>
>>>> Model     Num_var_gr1     num_var_gr2  num_var_gr3  num_var_gr4
>>>>
>>>> gr2 gr3        1                           2                     0
>>>>                 0
>>>>
>>>> gr2 gr4
>>>>
>>>> gr1 gr2
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