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

["josemaria" <jmpsouza@usp.br>]

the p-value is the Wald test ( in general (x-E(e))/se(x)) or some 
transformation) and does not depend of the level proposed for the CI.
Jos� Maria
Jos� Maria Pacheco de Souza, Professor Titular (aposentado)
Departamento de Epidemiologia
Faculdade de Sa�de P�blica/Universidade de S�o Paulo
Av. Dr. Arnaldo, 715 cep 01246-904
S�o Paulo Brasil
fones   (11)3061-7747 (11)3061-7724 (11)3714-2403  (11)3768-8612
fax   (11)3082-2920  (11)3714-2403
www.fsp.usp.br/~jmpsouza
jmpsouza@usp.br

----- Original Message ----- 
From: "Diego Bassani" <diego.bassani@gmail.com>
To: "Statalist" <statalist@hsphsun2.harvard.edu>
Sent: Friday, October 12, 2007 4:04 PM
Subject: st: Why is there a fixed alpha for the P>|z| estimated with 
poisson?



> 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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