hi,
thanks nick and carlo..
I understand your point about the p value in the statout now. I am a
bit confused about some things i have read elsewhere
for example the following
http://compdiag.molgen.mpg.de/ngfn/docs/2003/nov/Exercises_Bootstrap.pdf
discusses non parametric bootstrap on page 4 and on page 5 it talks about
"The two-sided p-values are now calculated by determining the
percentage of situation where the
absolute value of the test statistics calculated from the groups with
permutated values is at least
as large as the absolute value of the test statistics calculated from
the original groups."..
and the following page
westfall.ba.ttu.edu/Finance%20Pres.ppt
talks about something similar on page 11 and page 12
I am not what that means and how that is related to the stata p-value?
and the following page
westfall.ba.ttu.edu/Finance%20Pres.ppt
talks about something similar on page 11 and page 12
I am not what that means and how that is related to the stata p-value?
thanks
rich
2008/12/5 Carlo Lazzaro <[email protected]>:
> Dear Richard,
> I would refer you to Stata Archives and recommend to take a look at Maarten
> Buis' and Martin Weiss' kind replies to one thread I have posted on 2008 Sep
> 6 (which was not so different from yours, as it would seem):
>
> st: z statistics in bootstrap output
>
> Kind Regards and enjoy your W-E,
> Carlo
> -----Messaggio originale-----
> Da: [email protected]
> [mailto:[email protected]] Per conto di Richard Harvey
> Inviato: venerdì 5 dicembre 2008 18.40
> A: [email protected]
> Oggetto: st: bootstrapped p-values
>
> Hi,
>
> Could someone please explain how stata computes the bootstrap p-values?
>
> suppose i issue the following commands
>
> sysuse auto
> bootstrap t=r(t), rep(1000) saving(bsauto, replace): ttest mpg==0
>
> i get
>
>
> Bootstrap results Number
> of obs= 74
> Replications = 1000
>
>
> Observed Bootstrap Normal-based
> Coef. Std. Err. z P>z [95% Conf. Interval]
>
> t 31.66644 2.900212 10.92 0.000 25.98213 37.35075
>
>
> how does stata compute the P>z?
>
> does it...
>
> look at the proportion of bootstrapped t-values which are less than or
> equal to the original t-value ( from
> ttest mpg==0) say x and the proportion of bootstrapped t-values which
> are greater than or equal to the original t-value ( from ttest mpg==0)
> say y then computes p as 2 min(x,y) ?
>
> --
> thanks for your time
> rich
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>
>
>
> *
> * For searches and help try:
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>
--
thanks for your time
rich
*
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