--- Eva Batistatou wrote:
> I run some simulations and after regression analysis on 5,000 simulated
> datasets,I calculate the mean slope b and mean standard error of b's.We know
> that the mean SE(b)=standard deviation(b1,...,b5000).However,when instead of
> reporting the mean SE,I calculate the SD of b's,I find different results.Is it
> possible that this has to do with how STATA calculates the standard errors??
On possibility you have to take into account that simulations contain a
random component, so what you see may be the result of that. One way to
get a grip on that is to simulate the simulations, as is shown in the
example below. This example indicates that although the two statistics
can differ in individual simulations, there does not seem to be any
systematic difference between the two, indicating that these differences
are just due to the randomness of the simulation process.
*-------------- begin example -------------------
capture program drop Sim
program define Sim, rclass
drop _all
set obs 500
gen x = invnorm(uniform())
gen y = x + invnorm(uniform())
reg y x
return scalar b = _b[x]
return scalar se = _se[x]
end
capture program drop Simsim
program define Simsim, rclass
simulate b = r(b) se=r(se), reps(500) : Sim
/*Mean of se should be close to Std. Dev. of b*/
sum b
tempname bsd
scalar `bsd' = r(sd)
sum se
return scalar diff = r(mean) - `bsd'
end
simulate diff = r(diff), reps(500) : Simsim
sum diff
kdensity diff
*---------------- end example -------------------
(For more on how to use examples I sent to the Statalist, see
http://home.fsw.vu.nl/m.buis/stata/exampleFAQ.html )
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
*
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