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  • Command to use svy: tab by groups

    Hello,

    I have the dataset below and I use the command svy: tab i_aidhh if i_sex==2, col to identify female that took care of people (cg_aidhh) during the period in analyses. I would like to know the command to give the same answer (using the svy) but separeted by ages (variables: i_agegr10_dv). Can you help me with this? Thank you in advance.

    Code:
    * Example generated by -dataex-. To install: ssc install dataex
    clear
    input long(pidp pid) byte(i_sex i_aidhh i_agegr10_dv)
     749776175        -8 1 2 2
    1226092375        -8 1 2 2
      68903735        -8 2 2 2
     816392371        -8 2 2 2
     476632415        -8 2 2 2
    1361071019        -8 1 2 2
    1565029535        -8 1 2 2
     818669693 124195539 2 2 2
     613187295        -8 2 2 2
     205138335        -8 2 2 2
     544735783        -8 2 2 2
     749782977  93371306 2 2 2
     340799699        -8 2 2 2
     272537227        -8 1 2 2
     822562126        -8 2 2 2
     340449503        -8 1 2 2
     409305615        -8 2 2 2
    1020697695        -8 2 2 2
     272167291        -8 1 2 2
    1020783375        -8 2 2 2
     408102027        -8 2 2 2
    1156581423        -8 2 2 2
    1088523615        -8 2 2 2
    1156363819        -8 1 2 2
    1089022055        -8 2 2 2
    1443368130        -8 1 2 2
     816492335        -8 2 2 2
    1293054011        -8 2 2 2
     272039455        -8 2 2 2
     408423655        -8 2 2 2
     136195855        -8 2 2 2
     545073739        -8 2 2 2
     756452534        -8 2 2 2
    1157109775        -8 1 2 2
     408664375        -8 2 2 2
    1225441615        -8 2 2 2
    1292876539        -8 2 2 2
    1360218295        -8 2 2 2
     139387089  86432559 2 2 2
      68197903        -8 1 2 2
     409305619        -8 2 2 2
     776221373 119314428 2 2 2
     204533819        -8 2 2 2
     341187973  91942799 2 2 2
     750116173 113721722 1 2 2
    1292149615        -8 2 2 2
    1497727223        -8 2 1 2
     748973099        -8 2 2 2
     410390219        -8 1 2 2
    1156923455        -8 2 2 2
    1020303291        -8 2 2 2
     408790171        -8 1 2 2
    1433331334        -8 2 2 2
    1564873819        -8 2 2 2
    1099682570        -8 2 2 2
     272689535        -8 2 2 2
     204757539        -8 2 2 2
    1578286930        -8 1 2 2
    1156289695        -8 1 2 2
    1632393059        -8 2 2 2
     613303575        -8 2 2 2
    1496734419        -8 1 2 2
     340358383        -8 2 2 2
     694471773  95030174 2 2 2
    1294376615        -8 2 2 2
     136097255        -8 2 2 2
     544280171        -8 1 2 2
     411557773  83780807 2 2 2
      68412095        -8 2 2 2
     411286453 102719918 2 2 2
    1429168935        -8 2 2 2
     683337457 113050585 2 2 2
     342505815        -8 1 2 2
    1428614739        -8 1 2 2
     748450863        -8 2 2 2
    1088641259        -8 2 2 2
     273748301  87061678 2 2 2
    1224123783        -8 2 2 2
    1021003019        -8 2 2 2
    1175386930        -8 1 2 2
      69625893  86066978 2 2 2
    1293130179        -8 1 2 2
     408423651        -8 1 2 2
    1158289575        -8 1 2 2
     817871375        -8 2 2 2
     694471777 105781398 1 2 2
     885066255        -8 1 2 2
    1175386890        -8 1 2 2
     884805819        -8 2 2 2
      89129665 107106965 2 2 2
     612985335        -8 2 1 2
     884308739        -8 2 2 2
      69646293 102702845 1 1 2
    1034048930        -8 2 2 2
     137642221 102694095 2 2 2
     544180211        -8 2 2 2
    1429297455        -8 2 2 2
      68970375        -8 1 2 2
    1020317575        -8 1 2 2
    1236036210        -8 2 2 2
    end
    label values pid pid
    label def pid -8 "inapplicable", modify
    label values i_sex i_sex
    label def i_sex 1 "male", modify
    label def i_sex 2 "female", modify
    label values i_aidhh i_aidhh
    label def i_aidhh 1 "Yes", modify
    label def i_aidhh 2 "No", modify
    label values i_agegr10_dv i_agegr10_dv
    label def i_agegr10_dv 2 "10-19 years old", modify
    Best regars
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