I would think that you would need distinct models for the probability of
a zero and for the the conditional non-zero distribution. Perhaps
something like -heckman- might work. Even if the zero is not important,
you can't use something like a normal distribution to model the variable
unconditionally.
AL Feiveson
-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
Sent: Tuesday, September 05, 2006 2:07 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: Dependent variable [with zero mass point]
Without more known about the underlying science, it is difficult to
comment.
But one answer is that you don't necessarily need to do anything
special. It is the conditional distribution of response given predictors
that is the stochastic side of modelling, not the unconditional
distribution. Besides, a spike near the middle is not much of a
pathology compared with one at an extreme.
Incidentally, claims to urgency usually don't work: see the well meant
advice at http://www.catb.org/~esr/faqs/smart-questions.html#urgent
Nick
n.j.cox@durham.ac.uk
Francesca Gagliardi
> I would be grateful if anyone could give me suggestions on how to deal
> with a dependent variable that has a mass point at zero and is
> continuosly distributed over negative and positive values. In such a
> case, which is the most appropriate model to estimate?
>
> It is really important for me to solve this problem as soon as
> possible and I thank in advance for any help you would give me on this
> matter.
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