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st: Computing the proportion of significant variables after running numerous regressions
From
George Murray <[email protected]>
To
[email protected]
Subject
st: Computing the proportion of significant variables after running numerous regressions
Date
Sun, 13 May 2012 22:06:42 +1000
Dear Statalist,
I am using the -foreach- command to run approximately 1000
(bootstrapped) regression models, however I require an efficient way
of calculating the proportion of the regression models which have a
statistically significant constant at the 5% level; and of the
constants which are statistically significant, the proportion which
are positive. Below each of the 1000 regressions I run, a table is
displayed with the following format:
---------------------------------------------------------------------------------------------------
| Observed Bootstrap
V0 | Coef. Bias Std. Err.
[95% Conf. Interval]
-------------+------------------------------------------------------------------------------------
V1 | .00968169 -.0000537 .00057051 .008721 .0111218 (BC)
V2 | -.00110469 .0000782 .000691 -.0023101 .000459 (BC)
V3 | .00468313 -.0001562 .00084971 .0031954 .0064538 (BC)
_cons | -.00076976 .0001811 .00176677 -.0044496 .0025584 (BC)
--------------------------------------------------------------------------------------------------
I would be *very* grateful if someone knew the commands which would
allow me calculate this. In the past, I have used (a highly tedious
and embarrassing approach on) Excel where I filtered every Nth row,
and wrote a command to display 1 if the coefficient lies within the
confidence interval, and 0 if not. This time, however, I am running
numerous models and require a quicker approach.
One more question -- is there a way to create a new variable where the
coefficients of V1 (for example) are saved, so I can calculate the
mean, standard deviation etc.of V1?
If someone could answer at least one of these two questions, it would
be very much appreciated.
George Murray.
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