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Re: st: count data truncated at one

From   David Hoaglin <>
Subject   Re: st: count data truncated at one
Date   Mon, 11 Jun 2012 22:39:30 -0400


If people were included because they paid 2, 3, ..., 10 times a
reference number, the multiple does not look like the value of a
dependent variable.  Instead, it looks like the definition of 9
subgroups.  If the regression model is trying to predict the subgroup
that a person belongs to, -ologit- may be an appropriate approach,
especially with the higher frequency at 10x.

David Hoaglin

On Mon, Jun 11, 2012 at 9:01 PM, Laurie Molina <> wrote:
> Nick,
> Thanks for your repply.
> Yes, there are structural reasons why only those responses are possible.
> People included in the regression are members of a group defined as
> people paying 2 to ten times a reference number.
> I was thinking in ologit, but as there is cardinality involved, I was
> looking for a method that would consider all the available
> information, that is a method that would consider both the cardinal
> and ordinal properties of my data.
> I was thinking on reescaling the dataset so that 2 becomes 0, 3
> becomes 1, and so on. I know that this would not solver the high
> frequency of 10's (8's after reescaling), but I think my coefficients
> will still consistently estimate population parameters, as maximum
> likelihood estimation with poisson is robust to incorrer
> especification of the distribution as long as the conditional
> expectation function is correctly specified...
> Would it be terrible to do such a reescalation?
> Thank you again!
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