Roger Newson replied to Fred Wolfe
> >Is there anyway to get -parmby- output to include beta
> (Beta), as in:
> >
> > parmby "reg cutdown high pain_ haq_ depress glb age sex
> edlevel white
> > inctouse duration, beta", saving(testme, replace)
> for(estimate min95
> > max95 %8.2f p %8.1e) li(*)
>
> This is not a simple thing to do, because -regress- does
> not save any such
> estimation result as -e(Beta)-. However, you could always
> standardise your
> Y- and X-variables before doing your regression, as in the
> following program:
>
> foreach X of var cutdown high pain_ haq_ depress glb age
> sex edlevel white
> inctouse duration {
> summ `X'
> replace `X'=(`X'-r(mean))/r(sd)
> }
> parmby "reg cutdown high pain_ haq_ depress glb age sex
> edlevel white
> inctouse duration, beta", saving(testme, replace)
> for(estimate min95 max95
> %8.2f p %8.1e) li(*)
>
> This would code all your Y- and X-variables to a scale of
> SDs from the
> mean, causing -estimate-, -min95- and -max95- to be
> expressed in Y-axis SDs
> per X-axis SD. To eliminate missing values listwise, you
> might type instead:
>
> gene byte listmiss=0
> foreach X of var cutdown high pain_ haq_ depress glb age
> sex edlevel white
> inctouse duration {
> replace listmiss=1 if missing(`X')
> }
> foreach X of var cutdown high pain_ haq_ depress glb age
> sex edlevel white
> inctouse duration {
> replace `X'=. if listmiss
> summ `X'
> replace `X'=(`X'-r(mean))/r(sd)
> }
> parmby "reg cutdown high pain_ haq_ depress glb age sex
> edlevel white
> inctouse duration, beta", saving(testme, replace)
> for(estimate min95 max95
> %8.2f p %8.1e) li(*)
>
> This would recode all your X- and Y-variables to missing in
> observations
> where any of the variables were previously missing, or to a
> scale of SDs
> from the mean otherwise, where the SDs and means are from
> observations not
> deleted listwise.
A detail here is the markout of missing values.
Given
. local varlist "cutdown high pain_ haq_ depress glb age sex
edlevel white inctouse duration"
There are two other ways to mark out the observations
with any missings.
. reg `varlist'
. gen byte OK = e(sample)
or
. egen OK = rmiss(`varlist')
. replace OK = !OK
. qui foreach X of local varlist {
. su `X' if OK
. replace `X' = (`X' - r(mean)) / r(sd) if OK
. }
. parmby "reg `varlist'", saving(testme, replace)
for(estimate min95 max95 %8.2f p %8.1e) li(*)
Nick
[email protected]
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