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


From   Nick Cox <[email protected]>
To   [email protected]
Subject   Re: st: tuples, stepwise and counting types of variables
Date   Tue, 14 Aug 2012 02:45:14 +0100

In general, I don't regard myself as committed to supporting you in
doing something I recommended against!

In this case, I imagine you have to extract the names of predictors
used from the marginal names of e(b) or e(V). See also -indeplist-
(SSC).

Nick

On Tue, Aug 14, 2012 at 2:33 AM, Thomas Sohnesen <[email protected]> wrote:
> 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 <[email protected]> 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 <[email protected]> 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 <[email protected]> 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 <[email protected]> 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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