st: dropped observations in bootstrap

[Michael McCulloch <mm@pinest.org>]

Hello, I'd appreciate some guidance on this problem.

I'm running a weighted Cox regression within a bootstrap program.
If I conduct the analysis program, step by step outside the bootstrap 
it runs just fine.
However, when I conduct the exact same analysis within the bootstrap 
program, I get the error message:

"Bootstrap replications (50)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx    50
insufficient observations to compute bootstrap standard errors
no results will be saved
r(2000);"

What I'd like to learn is: how can I discover what happened to those 
observations during the bootstrap program? Note that these 
observations are not dropped during the manual analysis outside the 
bootstrap program.

I've illustrated my code below, using an adapted version of Stata's 
system data file cancer.dta.
Note: PART 1 I'm simply setting up cancer.dta for my analysis. My 
code in question is PART 2 below.


* PART 1
sysuse cancer, replace
ren died failed
tab drug
gen newdrug=0
replace newdrug=1 if drug==2|drug==3
drop drug
rename newdrug drug
tab drug

gen yeartreated=2007
gen monthtreated=10
gen daytreated=05

gen addyear=0
replace addyear=1 if studytime>=12 & studytime<24
replace addyear=2 if studytime>=24 & studytime<36
replace addyear=3 if studytime>=36

gen addmonths=0
replace addmonths=studytime-12 if studytime>=12 & studytime<24
replace addmonths=studytime-24 if studytime>=24 & studytime<36
replace addmonths=studytime-36 if studytime>36

gen yeardied=2007
replace yeardied= yeartreated + addyear if addyear!=0
list yeartreated yeardied addyear

gen monthdied=10
replace monthdied = monthtreated + addmonths if addmonths!=0
list monthtreated monthdied addmonths
replace yeardied=yeardied+1 if monthdied>=12 & monthdied<24
gen newmonthdied=monthdied
replace newmonthdied=monthdied-12 if monthdied>=12 & monthdied<24
replace newmonthdied=monthdied-24 if monthdied>=24
drop monthdied
gen monthdied = newmonthdied
drop newmonthdied

gen daydied=05

replace monthdied=monthdied+studytime if studytime<12
replace yeardied=yeardied+1 if monthdied>12
replace monthdied =monthdied-12 if monthdied>12

gen datedx = mdy(monthtreated, daytreated, yeartreated)
format datedx %d

gen datedied = mdy(monthdied, daydied, yeardied)
format datedied %d

sort datedied

list datedx datedied studytime



* PART 2
capture program drop msm
	program define msm, rclass

	* fit the full model used in Traditional Cox
	logit drug age

	*estimate probability of treatment
	predict p_tcm_ALL
	gen p_notcm_ALL = 1-p_tcm_ALL if drug==0	//want 
p(drug) for both users and nonusers
	replace p_tcm_ALL =p_notcm_ALL if drug==0

	*create stabilized weight==P(A)/P(A|W)
	logit drug
	predict p_ALL
	gen p_noALL=1-p_ALL if drug==0
	replace p_ALL = p_noALL if drug==0
	gen wt_stab_ALL=p_ALL/p_tcm_ALL

	* stset the data
	stset datedied [iweight=wt_stab_ALL], failure(failed) 
origin(datedx) scale(30.4375)	/*wt: stabilized IPTW*/

	* cox
		stcox drug
	indeplist, local
	foreach var of varlist `X' {
		return scalar `var' = _b[`var']
	}

end 
set seed 12358
bootstrap drug=r(drug), eform reps(50): msm

display exp(-1.995311)


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