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st: RE: Test for statistical significance - flag Stata 9.2/SE


From   "Cornelius Nattey" <cornelius.nattey@nioh.nhls.ac.za>
To   "Carlo Lazzaro" <carlo.lazzaro@tin.it>, <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Test for statistical significance - flag Stata 9.2/SE
Date   Wed, 1 Sep 2010 14:36:33 +0200

Thanks Carlo that was insightful
Regards,
Cornelius

-----Original Message-----
From: Carlo Lazzaro [mailto:carlo.lazzaro@tin.it] 
Sent: Tuesday, August 31, 2010 6:44 PM
To: statalist@hsphsun2.harvard.edu
Cc: Cornelius Nattey
Subject: R: Test for statistical significance - flag Stata 9.2/SE

Cornelius may want to calculate a bootstrap two-sided p-value instead of
rely upon the results of a probably bad-behaving unpaired ttest (I would
assume that the manganese serum distribution in humans departs from
normality):
--------------- code begins------------------------------------------
set obs 100
g Manga_1=uniform()*1 
g Manga_2=uniform()*1 
ttest Manga_1 == Manga_2, unpaired unequal
return list
scalar tobs=r(t)
replace Manga_1=Manga_1-r(mu_1)+(r(mu_1)+r(mu_2))/2
replace Manga_2=Manga_2-r(mu_2)+(r(mu_1)+r(mu_2))/2
bootstrap r(t), reps(10000) nodots saving(C:\Documents and
Settings\carlo\Desktop\Manga_boot.dta, every(1) double replace) : ttest
Manga_1 == Manga_2, unpaired unequal
use "C:\Documents and Settings\carlo\Desktop\Manga_boot.dta", clear
g indicator =abs(_bs_1)>=abs(scalar(tobs))
sum indicator, mean
di "p_bootstrap =" r(mean)
---------------code ends------------------------------------------
For further details on bootstrap procedures, the mandatory reference is:
Efron B, Tibshirani RJ. An introduction to the bootstrap. NewYork: Chapman
and Hall, 1993.

HTH and Kind Regards,
Carlo
-----Messaggio originale-----
Da: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Cornelius Nattey
Inviato: martedì 31 agosto 2010 16.25
A: statalist@hsphsun2.harvard.edu
Oggetto: st: Test for statistical significance

Dear All,
I have two datasets of manganese blood levels taken in August and
November 2005. They were from the same community but mainly different
people in the community. There may have been some repeats but I do not
know how many if there were any. I have treated them as independent and
not paired tests.

What test should be applied to see if there is a statistically sig
difference? Is there a difference?

Thanks very much
Cornelius


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The views expressed in this email are, unless otherwise stated, those of the author and not those of the National Health Laboratory Services or its management. The information in this e-mail is confidential and is intended solely for the addressee.
Access to this e-mail by anyone else is unauthorized. If you are not the intended recipient, any disclosure, copying, distribution or any action taken or omitted in reliance on this, is prohibited and may be unlawful.
Whilst all reasonable steps are taken to ensure the accuracy and integrity of information and data transmitted electronically and to preserve the confidentiality thereof, no liability or responsibility whatsoever is accepted if information or data is, for whatever reason, corrupted or does not reach its intended destination.






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