Thank you Alan
I was thinkoing about confident intervals (ci) after regression
Thank you
Dejan
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Alan
Neustadtl
Sent: 02 December 2008 15:33
To: [email protected]
Subject: Re: st: Extract confident intervals (ci) after regression
You didn't specify what you want the lower and upper limits of.
Regardless, -regress- returns two matrices, e(b) a coefficient
vector and e(V) a variance-covariance matrix of the estimators. I don't
think there is an e(ci) matrix.
You can make use of the stored estimates by doing something like this:
local lbx1 = _b[x1] - invttail(e(df_r),0.025)*_se[x1] local ubx1 =
_b[x1] + invttail(e(df_r),0.025)*_se[x1]
local lbx2 = _b[x2] - invttail(e(df_r),0.025)*_se[x2] local ubx2 =
_b[x2] + invttail(e(df_r),0.025)*_se[x2]
local lb_cons = _b[_cons] - invttail(e(df_r),0.025)*_se[_cons]
local ub_cons = _b[_cons] + invttail(e(df_r),0.025)*_se[_cons]
di "X1 LL=`lbx1' " "UL="`lbx1'
di "X1 LL=`lbx2' " "UL="`lbx2'
di "B0 LL=`lb_cons' " "UL="`ub_cons'
Best,
Alan
On Tue, Dec 2, 2008 at 9:05 AM, Loncar, Dejan <[email protected]>
wrote:
> Dear all
> I would like to extract an e()-class result stored in a matrix after
> regression.I would like to have the upper and lower bound of the ci
> but it doesn't work
>
> reg y x1 x2
> matrix A=e(ci)
> svmat A, names(c
>
> Any tips
>
> Thank you
> Dejan
>
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