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From |
David Hoaglin <dchoaglin@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: count data truncated at one |

Date |
Mon, 11 Jun 2012 22:39:30 -0400 |

Laurie, 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 <molinalaurie@gmail.com> 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! * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: count data truncated at one***From:*Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com>

**References**:**st: count data truncated at one***From:*Laurie Molina <molinalaurie@gmail.com>

**Re: st: count data truncated at one***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: count data truncated at one***From:*Laurie Molina <molinalaurie@gmail.com>

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