Hi everyone,

I should use Stata to make a mediatior analysis. I used the SUEST and I should do the bootstrapping for the mediatior analysis.
My command is the following:


capture program drop bootmm
program bootmm, rclass
reg ca_zsm g_comp g_coop tam_bedienbarkeit alter beruf female nettoeinkommen bildungsabschluss
estimates store cognitive_absoprtion

reg C_pc_risiko C_bedenken_zsm C_pc_nutzen tam_bedienbarkeit alter beruf female nettoeinkommen bildungsabschluss
estimates store risiko

reg C_pc_nutzen C_bedenken_zsm C_pc_risiko tam_bedienbarkeit alter beruf female nettoeinkommen bildungsabschluss
estimates store nutzen

poisson sm_infos_zsm_cv c.C_bedenken_zsm c.C_pc_risiko c.C_pc_nutzen c.C_ca_zsm i.g_comp i.g_coop c.C_pc_risiko#c.C_ca_zsm c.C_pc_nutzen#c.C_ca_zsm c.C_bedenken_zsm#c.C_ca_zsm c.tam_bedienbarkeit c.alter c.female c.bildungsabschluss
estimates store social_media_infos

poisson persönliche_infos_cv c.C_bedenken_zsm c.C_pc_risiko c.C_pc_nutzen c.C_ca_zsm i.g_comp i.g_coop c.C_pc_risiko#c.C_ca_zsm c.C_pc_nutzen#c.C_ca_zsm c.C_bedenken_zsm#c.C_ca_zsm c.tam_bedienbarkeit c.alter c.female c.bildungsabschluss
estimates store persönliche_infos

poisson sensible_infos_cv c.C_bedenken_zsm c.C_pc_risiko c.C_pc_nutzen c.C_ca_zsm i.g_comp i.g_coop c.C_pc_risiko#c.C_ca_zsm c.C_pc_nutzen#c.C_ca_zsm c.C_bedenken_zsm#c.C_ca_zsm c.tam_bedienbarkeit c.alter c.female c.bildungsabschluss
estimates store sensible_infos

suest cognitive_absoprtion risiko nutzen social_media_infos persönliche_infos sensible_infos

return scalar indav1a = _b[cognitive_absoprtion_mean:g_comp]*_b[social_media_infos_sm_infos_zsm_:C_ca_zsm]
return scalar indav2a = _b[cognitive_absoprtion_mean:g_comp]*_b[persönliche_infos_persönliche_in:C_ca_zsm]
return scalar indav3a = _b[cognitive_absoprtion_mean:g_comp]*_b[sensible_infos_sensible_infos_cv:C_ca_zsm]
return scalar indav1b = _b[cognitive_absoprtion_mean:g_coop]*_b[social_media_infos_sm_infos_zsm_:C_ca_zsm]
return scalar indav2b = _b[cognitive_absoprtion_mean:g_coop]*_b[persönliche_infos_persönliche_in:C_ca_zsm]
return scalar indav3b = _b[cognitive_absoprtion_mean:g_coop]*_b[sensible_infos_sensible_infos_cv:C_ca_zsm]
return scalar indtotal = _b[cognitive_absoprtion_mean:g_comp]*_b[social_media_infos_sm_infos_zsm_:C_ca_zsm] + ///
_b[cognitive_absoprtion_mean:g_comp]*_b[persönliche_infos_persönliche_in:C_ca_zsm] + ///
_b[cognitive_absoprtion_mean:g_comp]*_b[sensible_infos_sensible_infos_cv:C_ca_zsm] + ///
_b[cognitive_absoprtion_mean:g_coop]*_b[social_media_infos_sm_infos_zsm_:C_ca_zsm] + ///
_b[cognitive_absoprtion_mean:g_coop]*_b[persönliche_infos_persönliche_in:C_ca_zsm] + ///
_b[cognitive_absoprtion_mean:g_coop]*_b[sensible_infos_sensible_infos_cv:C_ca_zsm]
end

bootstrap r(indav1a) r(indav2a) r(indav3a) r(indav1b) r(indav2b) r(indav3b) r(indtotal), bca reps(500): bootmm



But it did not work and I do not know, how I can solve this problem.
This is the error message that appears everytime:

. bootstrap r(indav1a) r(indav2a) r(indav3a) r(indav1b) r(indav2b) r(indav3b) r(indtotal), bca reps(500): bootmm
(running bootmm on estimation sample)

Jackknife replications (458)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 50
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 100
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 150
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 200
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 250
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 300
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 350
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 400
nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn 450
nnnnnnnn
insufficient observations to compute jackknife standard errors
no results will be saved
r(2000);



Can anyone help me?
I would be very very grateful.

Thanks in advance,
Sarah