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st: RE: mkspline and reg


From   "Maarten Buis" <M.Buis@fsw.vu.nl>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: mkspline and reg
Date   Wed, 1 Nov 2006 10:21:58 +0100

Sami:
One way to see if your approach makes sense is to create predicted values, graph them and 
see if they make sense, like in the example below. I think it follows your procedure and the 
graphs look fine.

HTH,
Maarten

*-------------- begin example ------------
sysuse auto, clear
mkspline mpg1 20 mpg2=mpg

gen forXmpg1 = foreign*mpg1
gen forXmpg2 = foreign*mpg2
reg price mpg1 mpg2 forXmpg1 forXmpg2 foreign

predict pricehat1
twoway line pricehat1 mpg if foreign==0, sort  || /*
    */ line pricehat1 mpg if foreign==1, sort  /*
    */ ytitle("predicted price") name(a) /*
    */ legend(label(1 "domestic") label(2 "foreign"))

gen mpg1b = mpg1 - 12
gen forXmpg1b = foreign*mpg1b
reg price mpg1b mpg2 forXmpg1b forXmpg2 foreign
    
predict pricehat2
twoway line pricehat2 mpg if foreign==0, sort  || /*
    */ line pricehat2 mpg if foreign==1, sort  /*
    */ ytitle("predicted price") name(b) /*
    */ legend(label(1 "domestic") label(2 "foreign"))
*--------------- end example ---------------


-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology 
Vrije Universiteit Amsterdam 
Boelelaan 1081 
1081 HV Amsterdam 
The Netherlands

visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z434 

+31 20 5986715

http://home.fsw.vu.nl/m.buis/
-----------------------------------------

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of stata_user stata_user
Sent: dinsdag 31 oktober 2006 23:28
To: statalist@hsphsun2.harvard.edu
Subject: st: mkspline and reg


I 've a variable age which takes values from 20 to 60,
I have an outcome y and a dummy variable represnting gender

I would like to fit a regresion model using linear splines, including an
interraction effect

I want to test if there are two different slopes before 40 and after 40, and
I am also interested on the intercept , I consider the following approach

1/ First create linear splines

mkspline age1 40 age2 = age

2/Second  in order to have intercept at age=40

generate age1a = age1 -40

3/
I fit a regression model

xi: regress y i.sex*age1a i.sex*age2

Could you please comment on this approach?

 

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