[R] Regression model when dependent variable can only take positive values
Thierry.ONKELINX at inbo.be
Tue Dec 6 14:15:54 CET 2011
Did you measure newborns? If not center age to a value that makes sense in relation with the range of age in your dataset. Then the intercept will be the height at the reference age. And most likeli non-negative.
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Thierry.Onkelinx op inbo.be
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Van: r-help-bounces op r-project.org [mailto:r-help-bounces op r-project.org] Namens Michael Haenlein
Verzonden: dinsdag 6 december 2011 14:09
Aan: r-help op r-project.org
Onderwerp: [R] Regression model when dependent variable can only take positive values
I would like to run a regression of the form lm(y ~ x1+x2) where the dependent variable y can only take positive values. Assume, for example, that y is the height of a person (measured in cm), x1 is the gender (measured as a binary indicator with 0=male and 1=female) and x2 is the age of the person (measured in years).
When I run a simple lm(y ~ x1+x2), I obtain an intercept value that is negative. I interpret that in a way that a person who is male (x1=0) and just born (x2=0), has a negative height. This evidently does not make sense. I therefore assume that my estimates might be biased and that I need to use some other form of estimation that takes account of the fact that
y>0 for all observations.
Could anybody please tell me which type of regression would be most recommendable for this type of analysis?
Thanks very much in advance,
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