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RE: st: Bootstrap

From   "Nick Cox" <>
To   <>
Subject   RE: st: Bootstrap
Date   Fri, 15 Aug 2003 10:32:09 +0100

Jeff Pitblado replied to Joao Pedro W. de Azevedo

> > I would like to know how I can save the bootstraped 95% confidence
> intervals
> > of a mean.  It would be best for me to save this either
> as a scalar or a
> > local, since I will be using these values to generate a
> special tabulation
> > of several variables.
> The conficence limits are saved in matrices in e().  From
> [R] bootstrap:
> 	e(ci_normal)	normal-approximation Conficence limits
> 	e(ci_percent)	percentile Conficence limits
> 	e(ci_bc)	bias-corrected Conficence limits
> 	e(ci_bca)	bias-corrected and accelerated
> Conficence limits

Joao Pedro then asked

> Is there any way that I can see all the available matrixs after the
> bootstrap command? I've tried matrix dir, but nothing come up.
> What about the mean value? Where is it saved?

Yes: you can type -ereturn list-. The mean itself is saved in e(b).

As said earlier, given your aim of producing tables, I think
you want to get these results into variables as soon as possible.
(An alternative would be to populate a matrix, but that is not
as general or as flexible.)

Here is one approach. It is not the only one, and it certainly
is not necessarily the best one. It is based on a guess that
you want to do something by groups, which may not be the case
at all.

It may well be possible to do something like this using Roger
Newson's -parmby- or using -statsby-. If so, Roger will no
doubt show the way.

For this example, I wrote a do-file. The basic idea is to

	initialise variables to hold results

	loop over possibilities {
		run bootstrap
		get e-class results
		put them into matrices
		put them into appropriate variables

	prepare variables for table

	table results

First, here is the file:

. type

sysuse auto, clear

levels rep78, local(levels)

gen mean = .
gen lower = .
gen upper = .

qui foreach l of local levels {
        bootstrap "summarize mpg if rep78 == `l', meanonly" ///
        r(mean) , reps(1000)
        mat m = e(b)
        replace mean = m[1,1] if rep78 == `l'
        mat ci = e(ci_normal)
        replace lower = ci[1,1] if rep78 == `l'
        replace upper = ci[2,1] if rep78 == `l'

format mean lower upper %7.2f

noi di _n as txt "{title:Bootstrap confidence limits}"
noi tabdisp rep78 if rep78 < ., c(mean lower upper)

. ru

Bootstrap confidence limits

Repair    |
Record    |
1978      |       mean       lower       upper
        1 |      21.00       16.46       25.54
        2 |      19.13       16.56       21.69
        3 |      19.43       17.95       20.91
        4 |      21.67       19.29       24.05
        5 |      27.36       22.14       32.59

Preparing variables so that you can produce your own tables
is the main theme of an article "Problems with tables,
Part I" to appear next month in the Stata Journal.


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