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Re: st: Why is there a fixed alpha for the P>|z| estimated with poisson?


From   "Tom Trikalinos" <ttrikalin@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Why is there a fixed alpha for the P>|z| estimated with poisson?
Date   Fri, 12 Oct 2007 16:35:37 -0400

I do not think there's anything peculiar in the posted output.

the p-value should not change - your threshold at which a given
p-value is considered "beyond chance" changes.

The CI boundaries change as they are supposed to (Note the breadth of
the corresponding CIs in your output).

tom

On 10/12/07, Diego Bassani <diego.bassani@gmail.com> wrote:
> Dear Statalist members,
>
>  I have realized that the p-value for the null hypothesis (regression
> coefficient = zero given that the rest of the predictors are in the
> model) does not change when level (CI) is altered.
> Why is the alpha for the p-value calculation in the z distribution
> fixed, and is this true for other regression models as well?
>
> Thanks
>
> Diego
>
> ______________________
> see below three examples with level set at 99, 90 and 95.
>
> xi3: poisson dep i.ind, vce(cluster _set) irr   level(99)
>
> Iteration 0:   log pseudolikelihood =   -21326.6
> Iteration 1:   log pseudolikelihood =   -21326.6
>
> Poisson regression                                Number of obs   =      39500
>                                                   Wald chi2(1)    =       3.03
>                                                   Prob > chi2     =     0.0819
> Log pseudolikelihood =   -21326.6                 Pseudo R2       =     0.0001
>
>                                 (Std. Err. adjusted for 8351 clusters in _set)
> ------------------------------------------------------------------------------
>              |               Robust
>     dep|        IRR   Std. Err.      z    P>|z|     [99% Conf. Interval]
> -------------+----------------------------------------------------------------
>  _Iind |   1.034227   .0200087     1.74   0.082     .9839511    1.087072
> ------------------------------------------------------------------------------
>
> . xi3: poisson dep i.ind, vce(cluster _set) irr   level(95)
>
> Iteration 0:   log pseudolikelihood =   -21326.6
> Iteration 1:   log pseudolikelihood =   -21326.6
>
> Poisson regression                                Number of obs   =      39500
>                                                   Wald chi2(1)    =       3.03
>                                                   Prob > chi2     =     0.0819
> Log pseudolikelihood =   -21326.6                 Pseudo R2       =     0.0001
>
>                                 (Std. Err. adjusted for 8351 clusters in _set)
> ------------------------------------------------------------------------------
>              |               Robust
>    dep |        IRR   Std. Err.      z    P>|z|     [95% Conf. Interval]
> -------------+----------------------------------------------------------------
>  _Iind |   1.034227   .0200087     1.74   0.082     .9957449    1.074196
> ------------------------------------------------------------------------------
>
> . xi3: poisson dep i.ind vce(cluster _set) irr   level(90)
>
> Iteration 0:   log pseudolikelihood =   -21326.6
> Iteration 1:   log pseudolikelihood =   -21326.6
>
> Poisson regression                                Number of obs   =      39500
>                                                   Wald chi2(1)    =       3.03
>                                                   Prob > chi2     =     0.0819
> Log pseudolikelihood =   -21326.6                 Pseudo R2       =     0.0001
>
>                                 (Std. Err. adjusted for 8351 clusters in _set)
> ------------------------------------------------------------------------------
>              |               Robust
>    dep |        IRR   Std. Err.      z    P>|z|     [90% Conf. Interval]
> -------------+----------------------------------------------------------------
>  _Iind |   1.034227   .0200087     1.74   0.082     1.001834    1.067668
> ------------------------------------------------------------------------------
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