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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: question on zero inflated regression |

Date |
Mon, 14 Feb 2011 10:13:12 +0000 |

A "significant P-value" is a form of words to avoid, although everyone statistically-minded knows what you mean. But a very low P-value could in principle be consistent with the opposite result that zeros tend to correspond to hotter nights. Inspecting the sign of the coefficient and plotting counts against minimum temperature are surely indicated. Whether you need both temperature-related variables is difficult to say, but you can run the various possible models and compare. Nick On Mon, Feb 14, 2011 at 10:04 AM, rachel grant <rachelannegrant@gmail.com> wrote: > Thanks for responding Owen, that is really helpful. I tried running > the regression using multiple predictors as inflation variables and > two were highly significant. (minimum temperature and degreedays: > degreedays being a derivative of minimum temperature). This is > biologically a sensible result because amphibians cannot move if the > temperature is low, hence generating a zero result. My question now > is: does the significant p value indicate that the zeroes are > generated by low minimum temperatures? If so this is a very > interesting observation. Is it now legitimate to run the model using > only min temp and degree days as inflation variables. Many thanks - > things are becomimg clearer. On 13 February 2011 21:41, Owen Gallupe <ogallupe@gmail.com> wrote: >> Seems to me that there are a number of ways you can go with this: >> >> 1) if you don't have a theoretical justification as to why there is an >> inflation of zeros, put in all variables as potential causes. >> 2) don't use the zero inflated model at all. If there is reason to >> suspect that the zero scores are simply part of the continuum of >> scores (as in, the same causal factors related to scores of 1, 2, >> etc., are the same factors as scores of zero but in varying degrees), >> then a standard negative binomial might be better. >> >> In my opinion, this is a theoretical question. On Sun, Feb 13, 2011 at 10:58 AM, rachel grant >>> I am trying to use Zero inflated models, my data are counts of >>> ampibians arriving at a breeding site per night. Most nights none >>> arrive or one, but some nights many arrive hence the data are >>> overdispersed and have excess zeroes. I am using zero inflated >>> negative binomial regression. What I am confused about is I have to >>> specify the inflation variable (ie the one that is generating the >>> excess zeroes). I have 7 predictor variable and have no clue which is >>> responsible for generating the zeroes, so what to put into the model >>> as the inflation variable? Thanks for reading this >>> * * 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/

**References**:**st: question on zero inflated regression***From:*rachel grant <rachelannegrant@gmail.com>

**Re: st: question on zero inflated regression***From:*Owen Gallupe <ogallupe@gmail.com>

**Re: st: question on zero inflated regression***From:*rachel grant <rachelannegrant@gmail.com>

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