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Dear all:
Many medical variables are correlated, so I'm using the bootstrap
program to verify the most
frequently extracted variables within a backward and forward algorithm.
In the example below Nyha4 is by far the most extracted variable and
therefore the most significant statistically.
I usually publish tables of the selected variables with their
confidence limits.
I imagine that the bias corrected confidence limits provided by
bootstrap are the most correct ones.
Nonetheless until now I have always published the normal confidence
limits, because the p-value can be easily controlled from reviewers,
using the formula to calculate the variance under the normality assumption:
(lnucl-lnlcl)/(2*1.96))^2 . // lnucl=log of upper C. L.
lnlcl=log of lower C. L.
I would like to know there is a method to calculate the p_value
starting from the BC confidence limits.
Also it is not clear to me if the reported bias is a quantity that
adds to the standard error or must be subtracted from the standard
error in calculating the variance.
The BC confidence limits are narrower. So i imagine that bias should
be subtracted from standard error because bias relates to the part of
measurement error that is casual.
Am I correct?
If it is so it is important to have a p-value for this estimate but
the calculation with the usual zeta= _b/_se assumes a normality
distribution. Is it valid in this setting ?
It woul'd be wonderful if someone has a routine to calculate the
different p-values starting from the ereturn list of the bootstrap
saved values or could show how to calculate BC related p-values.
. bootstrap "sw, pr(.1) pe(.05): stcox fsex AOI sonoreint age nyha4
CPRENF CPRESPF CPIABP" _b,reps(1000) dots
command: sw , pr(.1) pe(.05) : stcox fsex AOI sonoreint age
nyha4 CPRENF CPRESPF CPIABP
statistics: b_sesso = _b[fsex]
b_age = _b[age]
b_nyha4 = _b[nyha4]
................................................................................
>....
Bootstrap statistics Number of obs = 327
Replications = 1000
------------------------------------------------------------------------------
Variable | Reps Observed Bias Std. Err. [95% Conf. Interval]
-------------+----------------------------------------------------------------
b_fsex | 597 -.3829885 -.1357204 .138327 -.6546561 -.1113208 (N)
| -.8652664 -.3303381 (P)
| -.4775621 -.2981049 (BC)
| -1.328869 .6971875 (BC)
b_age | 550 .0824691 .0245982 .0309384 .021697 .1432412 (N)
| .0681392 .1776492 (P)
| -.1053623 .1156664 (BC)
b_nyha4 | 845 1.043275 .2214171 .3910648 .2757012 1.810849 (N)
| .652275 2.103901 (P)
| .5398257 1.679764 (BC)
------------------------------------------------------------------------------
Note: N = normal
P = percentile
BC =
bias-corrected
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