hello statalisters,
I am fairly new to stata and still trying to get to grips with it. I recently encountered a problem with bootstrap difference in means test.
The code that I am using is based on several messages on the statalist. For example the one from brian poi of stata corp http://www.stata.com/statalist/archive/2004-04/msg00187.html. I have 10 numbers of such two group comparisions and this is my code.
for i=1(1)10 {
bootstrap r(t), reps(1000) seed(5432) saving(bs_1,replace):ttest var if gid==`i', by(group) unequal unpaired
bootout
}
* this will output the results in a table
*! version 1.0 a 25 jan 2010
capture program drop bootout
program define bootout
version 9
syntax
matrix b = e(b)
matrix se = e(se)
local names : colnames(se)
local df = e(N) - colsof(b)
tempname t lb ub
local i = 1
foreach var of local names {
scalar `t' = (b[1, `i'] / se[1, `i'])
scalar `lb' = b[1, `i'] - se[1, `i']*invttail(`df', 0.025)
scalar `ub' = b[1, `i'] + se[1, `i']*invttail(`df', 0.025)
di "`var'" _col(15) %9.0g b[1,`i'] ///
_col(26) %9.0g se[1, `i'] ///
_col(38) %6.2f `t' ///
_col(46) %6.3f 2*ttail(`df', abs(`t')) ///
_col(56) %9.0g `lb' ///
_col(68) %9.0g `ub'
local i = `i' + 1
}
end
Is this the right way to do this?
Also the above bootout prog assumes that the distribution of the bootstrapped t is normal. in otherwords the CI that i construct is based on a normal disribution.
How does one use the BCa or the percentile CI and work out a t statistic and p value for the difference in mean?
thanks
john
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