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Re: st: Creating categories of Continuous Variable


From   Richard Williams <[email protected]>
To   [email protected], [email protected]
Subject   Re: st: Creating categories of Continuous Variable
Date   Wed, 12 Mar 2014 20:15:06 -0500

You can check out the mkspline command. Besides the Stata docs, see

http://maartenbuis.nl/presentations/bonn09.pdf

http://www.stata.com/meeting/4nasug/RCsplines.pdf

http://www.ats.ucla.edu/stat/stata/faq/piecewise.htm

http://www.ats.ucla.edu/stat/stata/faq/nl_optimal_knots.htm

There are lots of other ways to deal with nonlinear relationships, e.g. If you suspect a curvilinear relationship you may wish to add an x^2 term.

http://essedunet.nsd.uib.no/cms/topics/multilevel/ch1/5.html


At 05:11 PM 3/12/2014, Satyen Dubey wrote:
Dear All,

I am examining the effect of "Y" variable on certain firm financial risk
variables. I am using OLS model to do this. My model looks like following.

Firm Risk Variable  = b+ "Y" + other variables

"Y" is a continuous variable and if theory holds should reduce firm risk.

Now i suspect that the effect of "Y" may not be the same for different
levels of "Y" e.g. for low values of "Y" the effect could be negative and
for high values (very extensive use) the effect could be positive.

To do this analyse I have created 5 dummy variables.
1) "Y"  <= 20% use then 1 otherwise 0
2) 20% < "Y" <= 40% then 1 else 0
3) 40% < "Y" <= 60% then 1 else 0
4) 60% < "Y" <= 80% then 1 else 0
5) "Y"  > 80% use then 1 otherwise 0

After  examine the following model.

Firm Risk Variable  = b+ "Y" *(1)+ "Y" *(2)+ "Y" *(3)+ "Y" *(4)+ "Y" *(5) +
other variables

My Questions is:

Is this correct way to do this?

Is there any other way i can examine this?

Thanks in advance.




-----
Thanks & Regards,

Satyen Dubey
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Richard Williams, Notre Dame Dept of Sociology
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