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From |
a b <andythezoologist@hotmail.com> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: FW: Standard error estimates lincom vs. estimates from predict command |

Date |
Mon, 14 Nov 2011 16:59:17 +0000 |

Dear Statalisters, There is probably a simple explanation (so patience might be required!) for this but I could not find an answer yet. I have a count data dataset which I modelled using a GLM with Poisson distribution and log link. I wanted to get standard errors to derive 95% CI for the predicted outcome values (i.e. each record in my dataset) (as an aside, I wanted to calculate the % coverage of the model estimates and the observed counts) So I used 'predict' with the xb option to get a linear prediction and the stdp option to get the standard error around the linear prediction. I then tried some combinations of the predictors in lincom lincom beta1*x + beta2*z ... + _cons and compared the predicted values and standard errors from lincheck and predict. While the predicted values were the same (as expected) from both, there was a very large difference between the standard errors (the standard errors being much larger from the predict stdp route). Can anyone tell me why this may be the case? And if I am testing the model using % coverage, which standard error I should derive my 95% CI from Any help would be much appreciated! * * 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/

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