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Re: st: different approaches to use only observations that have nonmissing


From   "Brent Fulton" <[email protected]>
To   <[email protected]>
Subject   Re: st: different approaches to use only observations that have nonmissing
Date   Wed, 25 Apr 2007 22:37:40 -0700

Dear Statalist,

I am using stata 9 and have a follow-up question to the above subject posted
in Oct. 2006. I am using a survey that asked whether a child was diagnosed
with ADHD (8% said yes, 92% said no), and if yes, asked whether the child
was taking medication. Hence, I wanted to know the appropriate way to code
the binary variable medication -medication-, which is currently missing for
92% of the sample. Hence, I created medication_nomissing where those 92%
observations are coded as 0.

gen medication_nomissing=medication
replace medication_nomissing=0 if adhd==0    /* this essentially changes
observations with missing medication to 0 */

gen valid= (adhd==1 & inlist(medication,0,1))  /* this was done per Jeff's
suggestion below and then implemented in model 3 */

I estimated these 4 models. Models 1, 2, and 3 report the same SEs for the
parameters and the same F, p for F, and dof for the model. Model 4 has
slightly different SEs and model statistics. The N, N_sub, and dof are shown
below.

/* model 1 */ svy: logit medication $independent
/* model 2 */ svy, subpop(if adhd==1): logit medication $independent
/* model 3 */ svy, subpop(if adhd==1): logit medication $independent if
valid
/* model 4 */ svy, subpop(if adhd==1): logit medication_nomissing
$independent

		N		N_sub		dof
model 1	5424		n/a		5373
model 2	5424		5424		5373
model 3	5424		5424		5373
model 4	75916		5424		75865

It seems that only model 4 is appropriate since it initially includes the
entire sample. I'd appreciate your suggestions.

Thanks,
Brent Fulton





http://www.stata.com/statalist/archive/2006-10/msg00740.html

Re: st: different approaches to use only observations that have nonmissing

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