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: [email protected]
[mailto:[email protected]] On Behalf Of Nick Cox
Sent: Tuesday, May 30, 2006 9:54 AM
To: [email protected]
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
[email protected]
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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*
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