# Re: st: how can I save confidence intervals, t and p values in macros?

 From Timothy.Mak@iop.kcl.ac.uk To statalist@hsphsun2.harvard.edu Subject Re: st: how can I save confidence intervals, t and p values in macros? Date Thu, 13 Jul 2006 12:18:34 +0100

```Thanks for your help.

Tim

Joseph Coveney <jcoveney@bigplanet.com>
Sent by: owner-statalist@hsphsun2.harvard.edu
13/07/2006 06:24
statalist@hsphsun2.harvard.edu

To
Statalist <statalist@hsphsun2.harvard.edu>
cc

Subject
Re: st: how can I save confidence intervals, t and p values in macros?

Maarten Buis wrote:

> i have checked the manuals and searched the help. e(b) gives the
> coefficient estimates, and e(V) gives the covariance of the
> estimates. But do I then have to calculate the p, the t, and the
> Confidence Intervals by hand?

> Otherwise, you will have to do it "by hand", which can
> be automated fairly easily depending on your ultimate goal.

Examples of automating these calculations can be found in earlier post
on the statalist, e.g.
http://www.stata.com/statalist/archive/2005-02/msg00481.html

--------------------------------------------------------------------------------

As Michael and Maarten mention, the task is fairly straightforward and has
come up on the list before.

If Tim is just putting the Wald t, p and CLs for each of the predictors
and
intercept of a single-equation linear model into a series of local or
global
macros, then it's scarcely more than a half-dozen lines of code for the
whole kit and caboodle.

Joseph Coveney

set more off
sysuse auto, clear
regress headroom trunk weight length turn
*
* Begin here
*
local predictor_list : colnames e(b) // Watch for dropped variables
foreach predictor of local predictor_list {
local t_`predictor' = _b[`predictor'] / _se[`predictor']
local p_`predictor' = 2 * ttail(e(df_r), abs(`t_`predictor''))
local half_alpha = (1 - `c(level)' / 100) / 2
local lcl_`predictor' = _b[`predictor'] + ///
invttail(e(df_r), 1-`half_alpha') * _se[`predictor']
local ucl_`predictor' = _b[`predictor'] + ///
invttail(e(df_r), `half_alpha') * _se[`predictor']
}
*
* Done
*
macro list
exit

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```