Dear Christian,
the following is a a fine-tuning of my yesterday's temptative answer to your
query, again not in Mata language.
Let's assume we have 20 + 20 sample means and sds (sample size: 10
observations each) drawn from 2 different populations (I mean, 20 from
population1 and 20 from population 2). Sample means and sds drawn from
population 1 are now labelled mean_alfa and sd_alfa. Sample means and sds
drawn from population 2 are now labelled mean_beta and sd_beta. Ttests are
performed under the equal variance assumption; hence, I have plugged in
pooled_variance formula (please, see v`i' line of the beneath reported Stata
9.2/Se .do file), as from Pagano M, Gavreau K. Principles of Biostatistics.
2nd edition. Brooks/Cole, 2000 (p 206 of the Italian edition).
Example now includes retrieving and storing two-sided p-value.
set obs 20
g mean_alfa=2*uniform()
g mean_beta=1*uniform()
g sd_alfa=.03*uniform()
g sd_beta=.02*uniform()
g double var_pooled=.
g double student_t=.
g double p_value=.
qui forval i = 1/20 {
qui g v`i'=((10-1)*sd_alfa[`i']^2+(10-1)*sd_beta[`i']^2)/(10+10-2)
sum v`i', meanonly
replace var_pooled=r(mean) in `i'
qui g t`i' = (mean_alfa[`i']-mean_beta[`i'])/(v`i'*(1/10+1/10))^.5
sum t`i', meanonly
replace student_t=r(mean) in `i'
qui g w`i'=ttail(18,abs(t`i'))
sum w`i', meanonly
replace p_value=r(mean) in `i'
drop v`i'
drop t`i'
drop w`i'
}
Again, not that elegant, but I do hope this help.
Kind Regards,
Carlo
-----Messaggio originale-----
Da: Carlo Lazzaro [mailto:[email protected]]
Inviato: sabato 4 luglio 2009 10.46
A: '[email protected]'
Cc: 'Christian Bustamante'
Oggetto: R: Mata question
Dear Christian,
the following is a temptative answer to your query, not in Mata language.
Let's assume we have 20 + 20 sample means and sds (sample size: 10
observations each) drawn from 2 different populations (I mean, 20 from
population1 and 20 from population 2). Sample means and sds drawn from
population 1 are labelled a and c. Sample means and sds drawn from
population 2 are labelled b and d. Ttests are performed under the equal
variance assumption. Example stops at Student t retrieving and storing for
each ttest performed (two-sided p-value was not included in the Stata .do
file).
set obs 20
g a==2*uniform()
g b=1*uniform()
g c=.03*uniform()
g d =.03*uniform()
g double student_t=.
qui forval i = 1/20 {
g t`i' = (a[`i']-b[`i'])/(c[`i']^2/10+d[`i']^2/10)^.5
sum t`i', meanonly
replace student_t=r(mean) in `i'
drop t`i'
}
Not that elegant, but I do hope this help.
Kind Regards,
Carlo
-----Messaggio originale-----
Da: [email protected]
[mailto:[email protected]] Per conto di Christian
Bustamante
Inviato: sabato 4 luglio 2009 9.15
A: Statalist
Oggetto: st: Mata question
Hi all
I'm trying to do a loot with a nested -ttesti- but I couldn't do it. I
have two vector with different means (m1 and m2) and another two with
each mean's standard deviation (s1 and s2). This vectors are quite
large, so do -ttesti- element for element could be very costly. Also,
I have each sample's size on two variables: n1 and n2. All this values
are obtained from a logistic regresion. After run -ttesti- I want to
save the t-statistic -r(t)- and the probability for two-sided p-value
-r(p)-. I'm doing something like this:
forvalues i=1/size(m1) { /* how can i get vector's size? */
ttesti n1 m1[1,`i'] s1[1,`i'] n1 m1[1,`i'] s1[1,`i']
mat tvalues[1,`i']=r(t)
mat pvalues[1,`i']=r(p)
}
But appears a lot of errors: 1) n1 should be integer. 2) 'm1' found
where number expected. 3) varlist not allowed.
How can I solve this?
Thanks
--
CdeB
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