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

 From Toby Andrew To statalist@hsphsun2.harvard.edu Subject Fwd: st: easy way to save regressor variable names? Date Mon, 13 Mar 2006 09:31:32 +0000

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).

```
```
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```
```
--
Rose Anne Medeiros
Department of Sociology / Family Research Laboratory
University of New Hampshire
126 Horton Social Science Center
Durham, NH 03824
U.S.A.

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```

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```