I don't follow this. Your results for diet show a P-value of 0.0407
which Stata is evidently happy to consider as < 0.05.
A quite separate point is that to many conservative statisticians your
P-values no longer have the orthodox interpretation after this shotgun
screening process.
Nick
[email protected]
Janet Hill
I have to run typically 50 variables separately in
ologit as part of a screening process and some of the
models fail with no convergence. I have tried the
following to trap the error and continue the analysis:
set more off
foreach x of var chew speech appear1 ......{
capture quietly ologit `x' wmean if surface==1
if _rc==0 & chi2tail(e(df_m),e(chi2)) < 0.05 di "`x'"
}
set more on
Hoping just to print out those variables with a model
probability < 0.05.
This typically produces several variables:
ache
diet
glass
etc.
When I subsequently analyse these variables the model
associated with ache has p<0.05, but diet does not
.. ologit ache wm if surface==1,nolog
Ordered logistic regression
Number of obs = 15
LR
chi2(1) = 4.83
Prob
> chi2 = 0.0280
Log likelihood = -16.888841
Pseudo R2 = 0.1251
------------------------------------------------------------------------
------
ache | Coef. Std. Err. z P>|z|
[95% Conf. Interval]
-------------+----------------------------------------------------------
------
wmean | 1.23758 .6219381 1.99 0.047
.0186035 2.456556
.. ologit ache wm if surface==1,nolog
.. ologit diet wm if surface==1,nolog
Ordered logistic regression
Number of obs = 15
LR
chi2(1) = 4.19
Prob
> chi2 = 0.0407
Log likelihood = -3.7955935
Pseudo R2 = 0.3556
------------------------------------------------------------------------
------
diet | Coef. Std. Err. z P>|z|
[95% Conf. Interval]
-------------+----------------------------------------------------------
------
wmean | -1.967477 1.24521 -1.58 0.114
-4.408044 .4730897
I would be grateful if somebody could point out my
programming error.
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