Hi StataList
I use Stata 14.1 on OSX.
I'm running a cost-effectiveness analysis and in order to get factors associated with costs, I run a twopart model using the twopm Stata command. It perfectly works.
The problem is I need to use both multiple imputations and bootstrapping (to get correct evaluations of CI).
That's why I've written the code below
But when I run the program bootstrapperso, the following message appears:
I've read several posts treating such a similar error message (like this one http://www.statalist.org/forums/search?r=42907686&p=12) but adding the no drop option did not change anything. Of course, I've not been able to run the mi estimate command.
Thank you for you help
I use Stata 14.1 on OSX.
I'm running a cost-effectiveness analysis and in order to get factors associated with costs, I run a twopart model using the twopm Stata command. It perfectly works.
The problem is I need to use both multiple imputations and bootstrapping (to get correct evaluations of CI).
That's why I've written the code below
Code:
/ evaluation first part to get OR & CI in appropriate format ***************program two-pm****************************** logistic charge $var_indep estout, c(b ci) drop(_cons) label eform matrix matrix_logistic = r(coefs) capture program drop boot_tpm_cond capture program define boot_tpm_cond, eclass // use second part to get conditional costs glm totalcharge_ccr $var_indep if totalcharge_ccr>0, /// link(log) family(poisson) margins , dydx(*) post end capture program drop boot_tpm capture program define boot_tpm, eclass // use stata twopm command to get unconditional costs twopm totalcharge_ccr $var_indep, /// firstpart(logit) /// secondpart(glm, link(log) family(poisson)) margins, dydx(*) nose post end ***************program two-pm****************************** ***************program bootstrap****************************** capture program drop bootstrapperso program define bootstrapperso, eclass // premier bootstrap : condtional margins bootstrap _b, reps($rep) seed(2) bca ties nodrop: boot_tpm_cond local n_reps_cond = e(N_reps) matrix b_cond = e(b) matrix ci_cond = e(ci_bca) // deuxieme bootstrap : unconditional margins bootstrap _b, reps($rep) seed(2) bca ties nodrop: boot_tpm local n_reps_uncond = e(N_reps) matrix b_uncond = e(b) matrix ci_uncond = e(ci_bca) end ***************program bootstrap****************************** ***************mi estimate sur l'ensemble****************************** mi estimate,noisily cmdok: bootstrapperso ***************mi estimate sur l'ensemble******************************
Code:
. bootstrapperso (running boot_tpm_cond on estimation sample) Jackknife replications (2085) ----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 50 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 100 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 150 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 200 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 250 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 300 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 350 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 400 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 450 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 500 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 550 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 600 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 650 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 700 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 750 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 800 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 850 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 900 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 950 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1000 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1050 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1100 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1150 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1200 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1250 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1300 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1350 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1400 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1450 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1500 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1550 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1600 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1650 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1700 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1750 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1800 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1850 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1900 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 1950 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 2000 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 2050 nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn insufficient observations to compute jackknife standard errors no results will be saved r(2000);
Thank you for you help
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