Dear all,

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,

Michael

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