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  • Create dataset - longitudinal

    Hello,

    I have a dataset (example below) where I use the command "append" to add the datasets: i_indresp, ce_indresp_w and cg_indresp_w.
    I nee to use the example of commands below to prepare the data in order to be a longitudinal data. However, I´m having dificulties in using this code to achieve the required results. Can you help me with this?
    Code that I need to use.

    foreach w in a b c d e {
    use `w'_indresp, clear
    renpfix `w'_
    gen wave=strpos("abcde", "`w'")
    save temp`w', replace
    }


    Example dataset:
    Code:
    * Example generated by -dataex-. For more info, type help dataex
    clear
    input long(pidp pid i_hidp) byte(i_pno i_sex) int i_dvage byte(cg_sex_cv ce_sex_cv ce_scghqa i_scghqa cg_scghqa cg_scghqd cg_scghqe)
       22445  10127798 277344816 1 2 33 . . .  2 . . .
       29925  10192697 619024416 1 2 40 . . .  1 . . .
       76165  10689869 141657616 1 2 34 . . .  2 . . .
      280165  12430439 754793216 1 2 38 . . .  2 . . .
      333205  12908843 415106696 1 2 26 . . .  2 . . .
      469205  13857142 415059096 1 2 27 . . .  2 . . .
      599765  14757249 211282816 1 2 30 . . .  2 . . .
      732365  15752658 619371216 1 1 32 . . .  4 . . .
     1587125  17870879 618269616 1 2 51 . . .  2 . . .
     1697285  42526507 210766016 1 1 44 . . .  2 . . .
     1833965  50832336 753508016 1 1 52 . . .  2 . . .
     2270525  76446336 823677216 1 2 20 . . .  3 . . .
     2626845  93565895 822997216 1 1 39 . . .  2 . . .
     2888645  96949503  76479616 1 2 28 . . .  2 . . .
     3587685 118781707 483813216 1 1 36 . . . -7 . . .
     3663845 119065835 416323216 1 1 33 . . . -8 . . .
     3667245 119074613 280309616 1 2 29 . . .  4 . . .
     3705325 119277506 144867216 1 2 63 . . .  2 . . .
     4454005 154358304 482840816 1 1 72 . . .  2 . . .
     4849085 176725733 347554816 1 1 34 . . .  4 . . .
     4853165 176977635 824289216 1 1 47 . . .  2 . . .
    68002045  10017933  73018416 1 2 74 . . . -8 . . .
    68002725  10023526  73025216 1 2 63 . . .  2 . . .
    68004087        -8  68006816 1 1 67 . . .  2 . . .
    68006127        -8  68013616 1 2 47 . . .  2 . . .
    68006807        -8  68034016 1 2 80 . . .  3 . . .
    68008847        -8  68040816 1 2 59 . . .  3 . . .
    68009527        -8  68047616 1 1 39 . . .  2 . . .
    68010887        -8  68054416 1 2 53 . . .  2 . . .
    68011567        -8  68061216 1 1 43 . . .  2 . . .
    68020407        -8  68095216 1 2 80 . . .  2 . . .
    68020564        -8  68013616 2 1 46 . . .  3 . . .
    68021765  10200436  73032016 1 2 58 . . .  4 . . .
    68021781  30139368  73032016 2 1 23 . . .  2 . . .
    68028567        -8  68108816 1 2 46 . . .  3 . . .
    68028571        -8  68108816 2 1 50 . . .  2 . . .
    68028575        -8  68129216 1 2 26 . . .  2 . . .
    68029927        -8  68136016 1 2 45 . . .  2 . . .
    68029931        -8  68136016 2 1 48 . . .  2 . . .
    68031967        -8  68142816 1 2 69 . . .  2 . . .
    68035365  10403086  73045616 1 1 65 . . .  2 . . .
    68035367        -8  68156416 1 1 36 . . .  2 . . .
    68036727        -8  68163216 1 1 85 . . .  2 . . .
    68037407        -8  68170016 1 2 48 . . .  2 . . .
    68041487        -8  68176816 1 2 47 . . .  3 . . .
    68041491        -8  68176816 2 1 44 . . .  1 . . .
    68042167        -8  68183616 1 1 47 . . .  2 . . .
    68042171        -8  68183616 2 2 46 . . .  2 . . .
    68043527        -8  68190416 1 1 63 . . .  2 . . .
    68044207        -8  68197216 1 2 42 . . .  3 . . .
    68044211        -8  68197216 2 1 44 . . .  2 . . .
    68044887        -8  68204016 1 2 70 . . .  2 . . .
    68045567        -8  68210816 1 2 55 . . .  1 . . .
    68045571        -8  68210816 2 1 57 . . .  2 . . .
    68046927        -8  68231216 1 2 44 . . .  2 . . .
    68046935        -8  68231216 2 2 17 . . .  2 . . .
    68048287        -8  68238016 1 1 70 . . .  2 . . .
    68049647        -8  68244816 1 1 59 . . .  2 . . .
    68049651        -8  68244816 2 2 57 . . .  2 . . .
    68051007        -8  68251616 1 1 56 . . .  1 . . .
    68051011        -8  68251616 2 2 49 . . .  3 . . .
    68056447        -8  68258416 1 1 54 . . .  3 . . .
    68056451        -8  68258416 2 2 52 . . .  2 . . .
    68056455        -8  68265216 1 2 22 . . .  3 . . .
    68056459        -8  68258416 3 2 17 . . .  2 . . .
    68058485  10628126  73052416 1 1 72 . . .  2 . . .
    68058487        -8  68272016 1 1 77 . . .  2 . . .
    68058489  10628169  73052416 2 2 72 . . .  2 . . .
    68058491        -8  68272016 2 2 68 . . .  3 . . .
    68059171        -8  68278816 1 2 27 . . .  2 . . .
    68060525  10641556  73059216 1 1 90 . . .  3 . . .
    68060527        -8  68285616 1 1 43 . . .  2 . . .
    68060531        -8  68285616 2 2 44 . . .  2 . . .
    68060533 160066204  73059216 2 2 61 . . .  3 . . .
    68060537 160066239  73059216 3 1 73 . . .  2 . . .
    68061288        -8  68047616 2 2 31 . . .  2 . . .
    68063247        -8  68292416 1 2 50 . . .  2 . . .
    68063251        -8  68292416 2 1 52 . . .  2 . . .
    68063255        -8  68292416 3 1 17 . . .  1 . . .
    68063927        -8  68299216 1 2 47 . . .  2 . . .
    68063931        -8  68299216 2 1 49 . . .  2 . . .
    68064605  10653872  73066016 1 1 68 . . .  2 . . .
    68064609  10653902  73066016 2 2 65 . . .  2 . . .
    68068007        -8  68326416 1 1 50 . . .  2 . . .
    68068011        -8  68326416 2 2 50 . . .  2 . . .
    68068015        -8  68327096 1 2 25 . . .  2 . . .
    68068082        -8  68054416 2 1 56 . . .  2 . . .
    68069367        -8  68333216 1 1 89 . . .  2 . . .
    68071407        -8  68340016 1 1 28 . . .  2 . . .
    68072087        -8  68346816 1 1 63 . . .  2 . . .
    68076167        -8  68360416 1 2 68 . . .  3 . . .
    68076171        -8  68360416 2 1 71 . . .  2 . . .
    68086371        -8  68367216 1 2 28 . . .  2 . . .
    68087727        -8  68380816 1 2 67 . . .  2 . . .
    68090447        -8  68387616 1 2 64 . . .  2 . . .
    68091127        -8  68394416 1 2 43 . . .  3 . . .
    68091135        -8  68401216 1 2 20 . . .  4 . . .
    68091139        -8  68394416 2 1 18 . . .  3 . . .
    68097245  10913629  73072816 1 2 67 . . .  2 . . .
    68097927        -8  68421616 1 2 68 . . .  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_dvage i_dvage
    label values cg_sex_cv cg_sex_cv
    label values ce_sex_cv ce_sex_cv
    label values ce_scghqa ce_scghqa
    label values i_scghqa i_scghqa
    label def i_scghqa -8 "inapplicable", modify
    label def i_scghqa -7 "proxy", modify
    label def i_scghqa 1 "Better than usual", modify
    label def i_scghqa 2 "Same as usual", modify
    label def i_scghqa 3 "Less than usual", modify
    label def i_scghqa 4 "Much less than usual", modify
    label values cg_scghqa cg_scghqa
    label values cg_scghqd cg_scghqd
    label values cg_scghqe cg_scghqe
    Thank you in advance

  • #2
    I don't understand the problem. You've got lots of datasets you've appended, I get that.

    I'll ask this way: what problem is your code trying to solve? What result is it meant to get?

    Comment

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