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RE: st: confidence intervals for ratio of predictions-- bootstrap vs. parametric methods?


From   "Daniel Waxman" <[email protected]>
To   <[email protected]>
Subject   RE: st: confidence intervals for ratio of predictions-- bootstrap vs. parametric methods?
Date   Fri, 12 Oct 2007 22:41:31 -0400

Uh oh.  This isn't right at all.

At least this has evolved into a more Stataish question...

Basically, rather than generate the variable "rr" which contains the
relative risk at all values of the continuous predictor "zlog", I would like
to bootstrap the relative risk at one discrete value of "zlog", with other
variables (some of which are continuous, some of which are dichotomous, not
shown in the previous example) adjusted in such a way that they reflect
their actual distribution in the data.

If anybody could point me in the right direction, I'd be most grateful.
(and I'd shut up).

Daniel


-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Daniel Waxman
Sent: Friday, October 12, 2007 9:32 PM
To: [email protected]
Subject: RE: st: confidence intervals for ratio of predictions-- bootstrap
vs. parametric methods?

For the record, I realized that I was bootstrapping the wrong thing.
Here is (a minimally simplified version) of what I meant to do ...

. boot
rr_univ=(invlogit($mb_notindicated_predictors)/invlogit($mbneg_predictors)),
/*
      */  reps($reps) saving(multiboot_notneg_$i,replace): /*
      */   logistic outcome zlog zero mbpos int_zlog_pos

. estat bootstrap

(no more red 'x's)

So the question was ... how to explain that these CIs
appear so much better than those generated as follows?

. logistic outcome zlog zero mbpos int_zlog_pos
. predictnl
rr=invlogit($mbpos_predictors)/invlogit($mbneg_predictors),se(se_rr)
. gen ub = rr + 1.96*se_rr
. gen lb = rr - 1.96*se

(and is it reasonable to assume that with a whole lot of reps, the
bias-corrected bootstrapped CIs are in fact better?)


Where:

. global mbpos_terms _b[_cons] + _b[int_zlog_pos]*`constant'  + /*
*/ _b[int_zero_pos] + _b[zlog]*`constant'  + _b[zero] + _b[mbpos]

. global mbneg_terms _b[_cons] + _b[zlog]*`constant' + _b[zero]


Perhaps the question is more clear now (?)


Daniel
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