Fwd: st: easy way to save regressor variable names?

[Toby Andrew <t.andrew@imperial.ac.uk>]

Apologies - please ignore my previous email.
A while loop solves the problem fine without having to reference the  
regression equation number.

bw,

Toby


local clist
local j = 1
while index("``j''","_")==0 {
 local clist `clist' ``j''
 local j = `j' + 1
 di "`clist' "
 }




Begin forwarded message:


> From: Toby Andrew <t.andrew@ic.ac.uk>
> Date: 12 March 2006 21:48:44 GMT
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: easy way to save regressor variable names?
>
> Thank you very much Rose & Nick for your help with this.
>
> The code seems to work just as you suggest  ...  except for mlogit  
> predictor variable names, which are duplicated for each outcome  
> factor level.
> Could you tell me how to reference equation numbers?  i.e. what do  
> i need to add to the following line of code:
>
> if B[1, `j'] != 0 & "``j''" != "_cons" {
> }
>
> so that only the variables listed in one of the factor equations  
> are saved in the macro list?
> Thanks,
>
> Toby
>
> ********************************************************************** 
> **
> Example output:
>
> Multinomial logistic regression                   Number of obs    
> =        841
>                                                   LR chi2(4)       
> =     256.37
>                                                   Prob > chi2      
> =     0.0000
> Log likelihood = -733.84352                       Pseudo R2        
> =     0.1487
>
> ---------------------------------------------------------------------- 
> --------
>          v54 |      Coef.   Std. Err.      z    P>|z|     [95%  
> Conf. Interval]
> ------------- 
> +----------------------------------------------------------------
> 0            |
>          v52 |   -1.30788   .3571904    -3.66   0.000      
> -2.00796   -.6077996
>          v59 |  -33.65493    3135026    -0.00   1.000      
> -6144572     6144505
>        _cons |  -.0186747   .0888481    -0.21   0.834    -. 
> 1928137    .1554643
> ------------- 
> +----------------------------------------------------------------
> 2            |
>          v52 |   .9150756   .2319136     3.95   0.000     . 
> 4605334    1.369618
>          v59 |   .1055173   .2495306     0.42   0.672    -. 
> 3835537    .5945883
>        _cons |  -1.522468   .1388951   -10.96   0.000     
> -1.794697   -1.250239
> ---------------------------------------------------------------------- 
> --------
> (Outcome v54==1 is the comparison group)
>
>  mat B=e(b)
>
> .mat lis B
>
> B[1,6]
>              0:          0:          0:          2:           
> 2:          2:
>            v52         v59       _cons         v52          
> v59       _cons
> y1    -1.30788  -33.654931  -.01867473   .91507565   .10551731    
> -1.522468
>
> . local clist
>
> . tokenize "`: colnames e(b)'"
>
> . forval j = 1/`= colsof(B)'  {
>   2. if B[1, `j'] != 0 &  index("``j''","_")==0 {
>   3. local clist `clist' ``j''
>   4. di "`clist'"
>   5. }
>   6. }
> v52
> v52 v59
> v52 v59 v52
> v52 v59 v52 v59
> ********************************************************************** 
> **
>
>
> On 12 Mar 2006, at 00:47, Rose Medeiros wrote:
>
>
> > Thank you Nick!
> >
> > Nick Cox wrote:
> >
> > > I want to comment on the code just posted.
> > > local cons "_cons"
> > > matrix define B = get(_b)
> > > local p : colfullnames e(b)
> > > local n = "`s(after)'"
> > > local r : list sizeof n
> > > local clist = " "
> > > forvalues j = 1/`r' {
> > >    scalar define c`j' = B[1,`j']
> > >    if (c`j'~=0) {
> > >        local newpred : word `j' of `p'
> > >        local clist : list clist | newpred
> > >    }
> > > }
> > > local p_list : list clist - cons
> > >
> > > Note that evaluating when you only need to copy is a source of  
> > > bugs. (This is one of the outputs of -njc-.) The result of
> > > local n = "`s(after)'"
> > > will be truncated to at most 80 characters
> > > as a side-effect of the evaluation.
> > > Also, "`s(after)'" may include options, -if-
> > > and -in- stuff, and indeed much else, so the number of words in  
> > > it may easily differ from the number of columns in e(b). Leave it  
> > > well alone for this problem.
> > > More a matter of style: there is some unnecessary copying and  
> > > setting up here. The code may be an extract from a longer code  
> > > chunk in which things are defined for
> > > later use, but as far as what is visible
> > > is concerned it can be slimmed down to
> > > mat B = e(b) tokenize "`: colnames e(b)'" local clist forval j =  
> > > 1/`= colsof(B)' { 	if B[1, `j'] != 0 & "``j''" != "_cons" { 		 
> > > local clist `clist' ``j''
> > > 	}
> > > }
> > > I wouldn't be surprised at a shorter way of doing it.
> > > Nick n.j.cox@durham.ac.uk
> > > Rose Medeiros
> > >
> > >
> > > > My answer to your first question will depend on the regression  
> > > > command used. (I say my answer, since someone else may have a  
> > > > better way of doing this.) After you run regress, if covariates  
> > > > are dropped for collinearity, they will appear in the  
> > > > coefficient vector (e(b)), but the coefficient value in the  
> > > > vector e(b) will be zero. For commands like logit, ologit, and  
> > > > mlogit, independent variables dropped for collinearity will not  
> > > > appear in the coefficient vector. So you have to accommodate the  
> > > > particular regression command used. Also note that the constant  
> > > > (_cons) will be in the coefficient vector, so you'll have to  
> > > > remove that as well. Below is some syntax that I've been using  
> > > > to do what you describe (the list of variables is returned as  
> > > > the local macro p_list), it appears to work, but I make no  
> > > > guarantees.
> > > > * -------- begin example when command is regress -----------
> > > > * run regress
> > > > local cons "_cons"
> > > > matrix define B = get(_b)
> > > > local p : colfullnames e(b)
> > > > local n = "`s(after)'"
> > > > local r : list sizeof n
> > > > local clist = " "
> > > > forvalues j = 1/`r' {
> > > >    scalar define c`j' = B[1,`j']
> > > >    if (c`j'~=0) {
> > > >        local newpred : word `j' of `p'
> > > >        local clist : list clist | newpred
> > > >    }
> > > > }
> > > > local p_list : list clist - cons
> > > > *-------- end example when command is regress -----------
> > > >
> > > > *-------- begin example when command is logit, ologit, or mlogit  
> > > > -----------
> > > > * run logit or mlogit
> > > > local p : colnames e(b)
> > > > local p_list : list p - cons
> > > > *-------- end example when command is logit, ologit, or mlogit  
> > > > -----------
> > > Toby Andrew
> > > > > 1) Is there a generic way to access the list of variable
> > > > names used
> > > > > in a regression such as regress, mlogit & ologit?
> > > > > The reason i ask is because i am performing many regressions  
> > > > > by  looping over variables & the list of recorded variables i save
> > > > > will differ from the *actual* list retained in the analysis
> > > > if there
> > > > > is collinearity (or i wish to use stepwise sw).
> > >
> > > *
> > > *   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/
> >
> > --
> > Rose Anne Medeiros
> > Department of Sociology / Family Research Laboratory
> > University of New Hampshire
> > 126 Horton Social Science Center
> > 20 College Road
> > Durham, NH 03824
> > U.S.A.
> >
> > *
> > *   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
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