I am looking for help on -glmdose-.
code:mat def tp1=(0/6/12/24/60)
glmdose m_age_atbirth m_ed_yr m_partner h_ed_yr c_sex c_age_mo_cat m_ever_born ///
bord country_ area m_place_delivery_cat, t(bf_mo) ///
gpscore(glmgpscore_1) predict(hat_treat_glm_1) sigma(sd_glm_1) ///
cutpoints(bf_mo_cat) index(p50) nq_gps(5) family(poisson) link(log) ///
outcome(mbdty_diarrhea_new) dose_response(doseresp_fl) tpoints(tp1) delta(6) ///
bootstrap(yes) boot_reps(10) analysis(yes) detail filename("output_log") graph("graphlog.eps")
error:Master Data not sorted
Data:
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float m_age_atbirth long m_ed_yr float m_partner long h_ed_yr byte c_sex float c_age_mo_cat byte(m_ever_born bord) long country_ byte area float m_place_delivery_cat long bf_mo float bf_mo_cat 15 5 1 7 1 0 1 1 18 1 . 4 0 22 7 1 10 1 24 2 2 50 1 20 15 12 20 0 1 4 1 12 2 2 8 1 10 16 12 27 2 1 0 1 24 6 5 52 1 10 12 12 23 9 1 2 2 0 1 1 40 1 20 3 0 22 14 1 11 2 6 1 1 40 1 20 4 0 26 4 1 10 1 0 2 2 6 1 20 2 0 35 16 1 16 2 0 3 3 50 1 20 0 0 37 17 1 . 2 12 3 3 29 1 20 6 6 20 9 0 . 2 12 1 1 48 1 10 18 12 30 12 1 12 1 0 3 2 30 1 20 2 0 19 11 1 11 2 12 1 1 31 1 20 12 12 43 6 1 9 1 6 6 6 39 1 20 6 6 27 15 1 15 1 24 1 1 40 1 20 18 12 30 12 1 12 2 24 4 4 32 1 10 24 20 25 15 1 11 1 24 1 1 40 1 20 4 0 25 9 1 . 1 12 2 2 29 1 20 13 12 24 3 1 4 1 24 2 1 40 1 20 17 12 21 12 1 11 2 12 1 1 50 1 20 17 12 28 12 1 10 1 24 1 1 40 1 20 7 6 26 11 1 12 1 24 2 2 19 1 20 24 20 16 0 1 9 1 24 1 1 29 1 10 46 20 26 8 1 8 1 24 2 1 40 1 20 18 12 32 6 1 9 1 24 3 3 19 1 10 30 20 33 11 1 10 1 12 3 3 50 1 20 16 12 23 9 1 9 1 24 1 1 40 1 20 1 0 29 0 1 10 1 6 5 5 41 1 10 7 6 18 10 1 7 1 24 2 1 29 1 20 24 20 25 11 1 14 2 24 3 2 40 1 20 6 6 28 12 1 9 2 0 2 2 29 1 20 2 0 21 2 1 5 1 12 2 2 16 1 20 17 12 22 12 1 14 2 0 1 1 30 1 20 4 0 28 10 1 . 1 6 3 3 29 1 20 11 6 24 13 1 16 1 0 2 2 50 1 20 2 0 23 11 1 9 1 12 1 1 58 1 20 20 20 25 11 1 14 2 0 1 1 19 1 20 3 0 26 16 1 10 1 12 2 2 40 1 20 14 12 24 17 1 19 1 24 1 1 40 1 20 7 6 24 8 1 9 2 24 3 2 40 1 20 0 0 25 1 1 5 2 24 4 4 29 1 20 25 20 23 17 1 15 1 24 1 1 29 1 20 9 6 24 16 1 16 1 24 2 1 19 1 20 20 20 23 14 0 . 2 0 1 1 50 1 20 5 0 24 9 1 13 1 0 1 1 40 1 20 2 0 30 13 . 10 2 24 2 2 40 1 20 7 6 37 0 0 8 2 0 2 2 27 1 20 2 0 22 12 1 12 2 12 2 2 25 1 20 17 12 25 13 . 15 2 24 3 3 40 1 20 1 0 25 9 1 13 1 0 2 2 40 1 20 1 0 20 9 1 9 1 24 1 1 40 1 20 6 6 33 0 1 8 1 24 6 5 10 1 10 18 12 32 6 0 0 1 24 3 3 50 1 20 18 12 30 13 . 15 2 24 1 1 40 1 20 4 0 25 10 1 7 1 24 4 3 51 1 10 15 12 26 15 1 15 1 24 1 1 29 1 20 12 12 20 9 1 9 2 24 2 1 30 1 10 14 12 42 6 1 6 1 0 8 8 48 1 20 5 0 23 5 1 4 1 24 2 2 30 1 10 59 20 21 9 0 9 1 24 1 1 40 1 20 23 20 24 12 1 12 2 12 1 1 40 1 20 3 0 31 10 1 15 1 6 2 2 29 1 20 10 6 22 9 1 11 2 24 2 2 13 1 20 9 6 36 3 1 4 1 24 5 5 46 1 20 24 20 34 17 1 17 1 6 2 2 27 1 20 9 6 30 13 . 13 2 24 2 2 40 1 20 3 0 21 0 1 12 1 0 1 1 16 1 20 3 0 29 10 1 10 2 12 2 1 40 1 20 7 6 31 15 1 9 2 12 3 3 3 1 20 15 12 35 15 1 15 2 24 4 3 29 1 20 18 12 31 12 1 12 2 12 1 1 40 1 20 13 12 35 10 1 12 1 0 2 2 51 1 20 1 0 24 12 1 . 1 0 3 3 29 1 20 2 0 31 9 1 10 1 12 3 3 40 1 20 6 6 24 8 0 . 1 24 3 3 32 1 20 12 12 25 6 1 . 2 24 2 2 29 1 20 26 20 26 9 1 12 2 0 4 4 48 1 10 3 0 41 6 1 9 2 12 10 10 30 1 10 21 20 26 7 1 . 2 6 2 2 29 1 20 9 6 20 12 0 . 2 24 1 1 40 1 20 18 12 18 11 1 11 2 0 1 1 19 1 20 5 0 24 8 1 . 1 12 3 3 29 1 20 15 12 29 0 1 0 1 12 6 6 54 1 20 16 12 22 5 1 0 2 12 1 1 49 1 10 19 12 31 13 . 12 2 24 2 2 40 1 20 1 0 27 9 1 9 2 24 2 2 19 1 20 15 12 32 9 1 11 2 0 3 3 50 1 20 4 0 24 17 1 . 2 24 2 2 29 1 20 12 12 20 15 1 15 2 24 3 2 29 1 20 6 6 25 0 1 0 2 24 4 2 8 1 10 24 20 40 13 1 16 2 24 7 7 11 1 20 15 12 22 8 1 9 2 24 5 4 40 1 20 16 12 21 7 0 11 2 0 3 3 13 1 20 3 0 29 4 1 11 2 24 4 3 6 1 20 18 12 38 10 1 13 1 6 3 3 40 1 20 6 6 23 8 1 11 1 0 1 1 19 1 20 0 0 30 15 1 13 1 12 2 2 40 1 20 12 12 25 7 1 10 2 12 4 4 21 1 20 16 12 21 9 1 11 2 24 2 2 29 1 10 17 12 21 7 1 . 2 24 1 1 29 1 20 31 20 30 15 1 15 1 24 3 3 40 1 20 8 6 end label values m_ed_yr V133 label values h_ed_yr V715 label values c_sex c_sex label def c_sex 1 "Male", modify label def c_sex 2 "Female", modify label values c_age_mo_cat c_age_mo_cat label def c_age_mo_cat 0 "0 - 5 months", modify label def c_age_mo_cat 6 "6 - 11 months", modify label def c_age_mo_cat 12 "12 - 23 months", modify label def c_age_mo_cat 24 "24 - 60 months", modify label values country_ country_ label def country_ 3 "Armenia", modify label def country_ 6 "Benin", modify label def country_ 8 "Burkina_Faso", modify label def country_ 10 "Cambodia", modify label def country_ 11 "Cameroon", modify label def country_ 13 "Colombia", modify label def country_ 16 "Congo_Democratic_Republic", modify label def country_ 18 "Dominican_Republic", modify label def country_ 19 "Egypt", modify label def country_ 21 "Ethiopia", modify label def country_ 25 "Guatemala", modify label def country_ 27 "Haiti", modify label def country_ 29 "India", modify label def country_ 30 "Indonesia", modify label def country_ 31 "Jordan", modify label def country_ 32 "Kenia", modify label def country_ 39 "Mali", modify label def country_ 40 "Moldova", modify label def country_ 41 "Morocco", modify label def country_ 46 "Nicaragua", modify label def country_ 48 "Nigeria", modify label def country_ 49 "Pakistan", modify label def country_ 50 "Peru", modify label def country_ 51 "Philippines", modify label def country_ 52 "Rwanda", modify label def country_ 54 "Senegal", modify label def country_ 58 "Tanzania", modify label values area area label def area 1 "Urban", modify label values m_place_delivery_cat m_place_delivery_cat label def m_place_delivery_cat 10 "Home Delivery", modify label def m_place_delivery_cat 20 "Hospital/Health Facility", modify label values bf_mo M5 label values bf_mo_cat bf_mo_cat label def bf_mo_cat 0 "0 - 5 months", modify label def bf_mo_cat 6 "6 - 11 months", modify label def bf_mo_cat 12 "12 - 23 months", modify label def bf_mo_cat 20 "24 - 60 months", modify
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