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Re: st: Using one variable to label another


From   Jeph Herrin <junk@spandrel.net>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Using one variable to label another
Date   Mon, 20 Nov 2006 07:48:01 -0500

Not efficient, but effective:

 local N=_N
 forv n=1/`N' {
	label define mylab v1[`n'] v2[`n'], modify
 }
 label values v1 mylab

If your dataset is large, you may want to first

 preserve
 bys v1 : keep if _n==1
 local N=_N
 forv n=1/`N' {
	label define mylab v1[`n'] "v2[`n']", modify
 }
 restore
 label values v1 mylab


hth,
Jeph


Doogar, Rajib wrote:
In Stat 9.2, how can I use the values of v2 (str 40, say) to label v1
(int)?  My data looks something like this:

V1      V2
1234    somerandomstring1
1234    somerandomstring1
2345    somerandomstring2
....
6578    somerandomstringn
....
etc.

I tried to encode v2 and then attach the resulting label to v1.  I
encoded v2 all right, but then got stumped by how correctly to link the
labels to the values of v1.  Encoding v2 gave me labels numbered 1 to
xxx, but v1 is a four digit number (although it does take exactly xxx
distinct values).

Many thanks!

Rajib Doogar,
Department of Accountancy,
The University of Illinois at Urbana-Champaign
1206 S. Sixth Street, Champaign, IL 61820
Ph: 217.244.8083, Fax: 217.244.0902
http://www.cba.uiuc.edu/doogar



-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
Sent: Tuesday, May 30, 2006 9:54 AM
To: statalist@hsphsun2.harvard.edu
Subject: RE: st: Calculating Percent Change In Regression Coeffecients

On a different note, why this interest in percent change in coefficient
as a metric?

I make three elementary comments.

1. The behaviour of ratios can be complicated already. This measure is a
ratio calculated from ratios.

2. Specifically, is the behaviour as the denominator goes from small
positive through zero to small negative regarded as a feature?

3. There is a lack of symmetry in the calculation.

I can imagine a practical argument that (1) and
(2) do not matter for the application, and (3) might be irrelevant given
a time order, but I wouldn't put much weight on this measure.

Nick
n.j.cox@durham.ac.uk

Tim Wade

Hi Raphael, I don't know how to do this in Mata, but here is a brute
force solution using macros and for loops:


. regress price headroom rep78 gear_ratio

      Source |       SS       df       MS              Number
of obs =      69
-------------+------------------------------           F(  3,
   65) =    4.68
       Model |   102521828     3  34173942.7           Prob >
F      =  0.0051
    Residual |   474275131    65  7296540.47
R-squared     =  0.1777
-------------+------------------------------           Adj
R-squared =  0.1398
       Total |   576796959    68  8482308.22           Root
MSE      =  2701.2

--------------------------------------------------------------
----------------
       price |      Coef.   Std. Err.      t    P>|t|
[95% Conf. Interval]
-------------+------------------------------------------------
----------------
    headroom |  -136.9778   414.9107    -0.33   0.742
-965.6117    691.6561
       rep78 |   576.2363   362.8717     1.59   0.117
-148.4686    1300.941
  gear_ratio |  -2995.126   829.7523    -3.61   0.001
-4652.256   -1337.996
       _cons |   13577.64   3025.567     4.49   0.000
7535.166    19620.12
--------------------------------------------------------------
----------------

/*only include coefficients you want to compare*/

. foreach var of varlist headroom rep78 {
  2. local `var'1=_b[`var']
  3. }

. regress price headroom rep78

      Source |       SS       df       MS              Number
of obs =      69
-------------+------------------------------           F(  2,
   66) =    0.43
       Model |  7450346.06     2  3725173.03           Prob >
F      =  0.6511
    Residual |   569346613    66  8626463.83
R-squared     =  0.0129
-------------+------------------------------           Adj
R-squared = -0.0170
       Total |   576796959    68  8482308.22           Root
MSE      =  2937.1

--------------------------------------------------------------
----------------
       price |      Coef.   Std. Err.      t    P>|t|
[95% Conf. Interval]
-------------+------------------------------------------------
----------------
    headroom |   391.6261   422.1074     0.93   0.357
-451.1385    1234.391
       rep78 |   69.23416   363.8024     0.19   0.850
-657.1208    795.5892
       _cons |   4735.368   1930.863     2.45   0.017
880.276    8590.459
--------------------------------------------------------------
----------------

. foreach var of varlist headroom rep78 {
  2. local `var'2=_b[`var']
  3. }

. foreach var of varlist headroom rep78 {
  2. di as result "percent change for
`var'="((``var'2'-``var'1')/``var'1')*100
  3. }
percent change for headroom=-385.90483 percent change for
rep78=-87.985109
Raphael Fraser

I would like to calculate the percentage change in the regression
coeffecients of model 1 and model 2. Can any one help? I tried using

Mata but I did not know how to divide each element in a matrix with
different scalars.

sysuse auto, clear
stset mpg, failure(foreign)
stcox mpg price weight rep78, nohr nolog /*Model 1*/ stcox mpg
weight rep78, nohr nolog /*Model 2*/

For example % change = (rep78_m2 - rep78_m1) / rep78_m1
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