victor michael zammit:
>mpg Coef. Std. Err. t P>t [95% Conf. Interval]
>
>weight -.0058175 .0006175 -9.421 0.000 -.0070489 -.0045862
>price -.0000935 .0001627 -0.575 0.567 -.000418 .0002309
>_cons 39.43966 1.621563 24.322 0.000 36.20635 42.67296
>
>
>can any one please tell me how I could retrieve the lower bound and the
>upper bound for 95% and 99% confidence intervals ?
>Yes. You can use the -parmest- package...
parmest sounds great, yet victor may want to retrieve the ci bounds more
directly. if he utilizes the general formula
u/lbound = point_estimate +/- z*se
(substitute z with the key deviant of the relevant distribution and the ci
width of your choice),
and the way to access estimation results in stata ([U] 21.9), he can go, e.g
di "upper bound: " _b[weight]-invttail(e(df_r),.975)*_se[weight]
or assign the result thereof to a local macro, etc.
note that -invttail- gives a negative result where some might expect a
positive one, hence a subtraction is called for when calculating the upper
bound. with other regressions using the z statistics, it is simpler as you
can use -invnorm(p)- which gives a positive deviant and involves no hassle
with the degrees of freedom. other listers please correct me if e(df_r) is
not the one really used in the above calculation - it is quite empirical
from my part but has so far seemed to work.
laszlo
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