Create a single table with information provided by xttab

[Ana Vasconcelos]

Hello,
I have a longitudinal dataset (5 waves) and I´m using the command by sex wave, sort: xttab unsafe_dv to look for the number of individuals by sex that answer "yes" and n"o" to unsafe_dv. The result is a sequence of tables with the required information. Is it possible to have a single table with all the information?
Thank y ou very much in advance.

* Example generated by -dataex-. For more info, type help dataex
clear
input long(pidp pid) byte sex float wave byte unsafe_dv
 633352005  97406155 2 1 .
 683918177  31845606 2 1 .
1157098895         . 1 1 .
 613171645  11302127 1 1 .
1564745971         . 2 1 .
 408423647         . 2 1 .
 217620484         . 1 1 .
 749100247         . 1 1 .
 816146215         . 1 1 .
  69869329  16778111 1 1 .
1156027211         . 1 1 .
1293664651         . 1 1 0
 816133967         . 2 1 .
1224690207         . 1 1 .
 435924205 118739549 1 1 .
1293398767         . 1 1 0
  70127049  18346677 2 1 .
 422150129  94933499 2 1 .
 172978482         . 2 1 .
 748584884         . 2 1 .
1360410051         . 2 1 .
 884158455         . 1 1 .
 544811247         . 2 1 .
 205445715         . 1 1 0
 136540609  14402327 2 1 .
  68740595         . 2 1 .
 204408011         . 2 1 .
1292913939         . 1 1 .
1225353282         . 2 1 .
 819397965  11892153 2 1 .
1292189059         . 1 1 .
1634644527         . 1 1 0
1428384887         . 2 1 .
 410598287         . 2 1 .
 273079167         . 2 1 .
 683372129  33188769 1 1 .
 891554882         . 2 1 0
 749161451         . 2 1 .
 205319209  10468056 2 1 .
 292674725  96945303 2 1 .
 632578165  97933848 2 1 .
 205916249 123559545 1 1 .
 748897724         . 1 1 .
 274509211         . 2 1 .
 340758211         . 1 1 .
1088426371         . 1 1 .
1497121327         . 1 1 .
 544184975         . 1 1 .
 274468411         . 2 1 .
1157062167         . 2 1 .
1088819427         . 1 1 .
1428334567         . 1 1 .
1496956767         . 2 1 .
 544240047         . 1 1 .
1428425011         . 1 1 .
1496985327         . 1 1 .
1020802411         . 1 1 .
  91810885 119261278 1 1 .
 680922091         . 1 1 .
1566525543         . 2 1 0
 614299089  76816591 2 1 .
 478639091         . 2 1 .
 546802967         . 1 1 .
1299195164         . 2 1 0
 416636284         . 2 1 .
1566423527         . 2 1 0
  68843887         . 1 1 .
 342501727         . 2 1 .
1428469887         . 1 1 0
 206572447         . 2 1 .
1088120367         . 1 1 .
 136066649  10669582 2 1 .
 476701771         . 2 1 .
 639238089 118758578 2 1 .
1224235295         . 2 1 .
1497122007         . 2 1 .
 476030609  10340416 2 1 .
 409332811         . 1 1 .
 884806491         . 2 1 .
1020639207         . 2 1 .
  70080125  16247396 2 1 .
1564837771         . 2 1 .
 476413451         . 2 1 0
1226738371         . 1 1 1
 884711295         . 2 1 .
1088091127         . 2 1 .
 292852885  96931248 2 1 .
 410527567         . 1 1 .
 272930257  17421942 2 1 .
 354131765  96051728 2 1 .
 410569047         . 2 1 .
 170326562         . 1 1 .
 612083647         . 2 1 .
 572229593 119318571 2 1 .
1157811527         . 2 1 0
 680359731         . 2 1 .
 340851369  16829611 2 1 .
  69177095         . 2 1 .
 204979207         . 1 1 .
 639380205 118898116 1 1 .
end
label values pid pid
label values sex c_sex
label def c_sex 1 "male", modify
label def c_sex 2 "female", modify
label values unsafe_dv c_unsafe_dv
label def c_unsafe_dv 0 "no", modify
label def c_unsafe_dv 1 "yes", modify

[Clyde Schechter]

If you are using version 17,

table (wave sex) (unsafe_dv)

[Ana Vasconcelos]

I´m using version 16 but it worked. Thank you very much!

[Ana Vasconcelos]

In relation to the first question: Is it possible to have the results in the same table using several variables (unsafe1, unsafe2, unsafe3)? I tred the command table (wave sex) (unsafe1 unsafe2 unsafe3) but it didn´t work. I send an example of the dataset below.
Thank you very much in advance.

* Example generated by -dataex-. For more info, type help dataex
clear
input long(pidp pid) byte sex float wave byte(unsafe1 unsafe2 unsafe3 unsafe4 unsafe5)
 476482809  13998242 1 5 0 0 0 0 0
 476482811         . 1 1 . . . . .
 410422845  11178973 1 1 . . . . .
 684705696         . 1 4 . . . . .
1089041767         . 1 1 . . . . .
1020389647         . 1 1 . . . . .
 546683287         . 1 4 . . . . .
 546337171         . 1 3 . . . . .
1633304251         . 1 1 . . . . .
 885615011         . 1 4 0 0 0 0 0
 693837393  94555281 1 1 . . . . .
1651883290         . 1 4 0 0 0 0 0
 342903734         . 1 4 . . . . .
 972345690         . 1 4 0 0 0 1 0
 816592971         . 1 1 . . . . .
 410492887         . 1 1 . . . . .
 136864291         . 1 1 . . . . .
1226405859         . 1 2 0 0 0 1 0
 816941131         . 1 3 . . . . .
 952089099         . 1 4 . . . . .
 544211495         . 1 3 . . . . .
1429125411         . 1 5 . . . . .
 477702727         . 1 3 0 0 0 0 0
  68383529  13280481 1 3 . . . . .
  71034853  91722071 1 3 . . . . .
 476495727         . 1 2 . . . . .
1088748687         . 1 1 . . . . .
1234934570         . 1 3 0 0 0 0 0
 558471085  94968195 1 1 . . . . .
 138154925  11564172 1 1 . . . . .
 952686811         . 1 4 . . . . .
 275957728         . 1 2 . . . . .
1632845931         . 1 1 . . . . .
 613676213  35671246 1 1 . . . . .
 749284531         . 1 2 . . . . .
 136569851         . 1 4 . . . . .
 476497783         . 1 1 . . . . .
1360282891         . 1 1 . . . . .
 476497783         . 1 3 . . . . .
 816975807         . 1 5 0 0 0 0 0
 204562371         . 1 3 . . . . .
1497101611         . 1 1 . . . . .
 960078602         . 1 3 0 0 0 0 0
 953241687         . 1 3 . . . . .
 817123371         . 1 1 . . . . .
 136667087         . 1 2 . . . . .
 476504571         . 1 1 . . . . .
1101076450         . 1 3 . . . . .
 545133571         . 1 1 . . . . .
1428504571         . 1 2 . . . . .
 476505247         . 1 3 . . . . .
 749470165  16277627 1 4 . . . . .
1632218287         . 1 2 . . . . .
1428017007         . 1 1 . . . . .
 953139007         . 1 3 0 0 0 0 0
 544604531         . 1 1 . . . . .
1020093171         . 1 3 . . . . .
 410131147         . 1 4 0 0 0 0 0
 163753525 118822969 1 3 . . . . .
 476131245  11205849 1 4 . . . . .
1564567135         . 1 3 . . . . .
1292182931         . 1 2 . . . . .
1428964247         . 1 1 . . . . .
 476514771         . 1 1 . . . . .
  69003687         . 1 2 . . . . .
 341338935         . 1 1 . . . . .
1158492887         . 1 1 0 0 0 0 0
 884398491         . 1 2 . . . . .
 476514779         . 1 2 . . . . .
1564605211         . 1 1 . . . . .
  95740605 118812769 1 3 . . . . .
 885993775         . 1 2 0 0 0 0 0
 340214895         . 1 5 0 0 0 0 0
1293752367         . 1 2 0 0 0 0 0
1292937731         . 1 1 . . . . .
  69062859         . 1 5 0 0 0 0 0
1428765011         . 1 2 . . . . .
 163809285 118544365 1 1 . . . . .
1633269567         . 1 5 0 0 0 0 1
  68813979         . 1 5 0 0 0 0 0
 476529727         . 1 3 . . . . .
1225584526         . 1 2 . . . . .
 749840767         . 1 1 0 0 0 0 0
 748669127         . 1 1 . . . . .
1293804731         . 1 5 0 0 0 0 0
1360196531         . 1 2 . . . . .
 545073731         . 1 5 0 0 0 0 0
 503911965 118726617 1 2 . . . . .
1224558299         . 1 4 . . . . .
 748552863         . 1 5 0 0 0 0 0
 476533127         . 1 5 0 0 0 0 0
 693727169  94549478 1 2 . . . . .
 817337577  56546289 1 2 . . . . .
1174094890         . 1 3 . . . . .
  70786653 163811504 1 4 . . . . .
 885111139         . 1 3 . . . . .
 272881967         . 1 1 . . . . .
 408391687         . 1 2 . . . . .
 273064211         . 1 3 . . . . .
 342016887         . 1 5 0 0 0 0 0
end
label values pid pid
label values sex c_sex
label def c_sex 1 "male", modify
label values unsafe1 c_unsafe1
label def c_unsafe1 0 "not mentioned", modify
label values unsafe2 c_unsafe2
label def c_unsafe2 0 "not mentioned", modify
label values unsafe3 c_unsafe3
label def c_unsafe3 0 "not mentioned", modify
label values unsafe4 c_unsafe4
label def c_unsafe4 0 "not mentioned", modify
label def c_unsafe4 1 "Mentioned", modify
label values unsafe5 c_unsafe5
label def c_unsafe5 0 "not mentioned", modify
label def c_unsafe5 1 "Mentioned", modify

[Clyde Schechter]

In version 17, it's quite simple:

table (wave sex) (var), statistic(fvfrequency unsafe*)
// OR
table (wave var) (sex), statistic(fvfrequency unsafe*)

depending on which way you want the results laid out.

But in version 16 or earlier, using only official StataCorp commands, I don't think you can generate that same kind of table. That said, there are a large number of user-written commands for creating tables and it may be that one of them can do this. I'm not very familiar with those commands and can't advise. I hope that somebody who knows one that fits the bill is following along and will intervene here.

[Nick Cox]

I am not especially clear what you want to see in your table, and naturally there are many possibilities. But groups from the Stata Journal will work in Stata 16.

Here is a token example. I simplified the value labels; otherwise there is awkward wrap-around.

* Example generated by -dataex-. For more info, type help dataex
clear
input long(pidp pid) byte sex float wave byte(unsafe1 unsafe2 unsafe3 unsafe4 unsafe5)
 476482809  13998242 1 5 0 0 0 0 0
 476482811         . 1 1 . . . . .
 410422845  11178973 1 1 . . . . .
 684705696         . 1 4 . . . . .
1089041767         . 1 1 . . . . .
1020389647         . 1 1 . . . . .
 546683287         . 1 4 . . . . .
 546337171         . 1 3 . . . . .
1633304251         . 1 1 . . . . .
 885615011         . 1 4 0 0 0 0 0
 693837393  94555281 1 1 . . . . .
1651883290         . 1 4 0 0 0 0 0
 342903734         . 1 4 . . . . .
 972345690         . 1 4 0 0 0 1 0
 816592971         . 1 1 . . . . .
 410492887         . 1 1 . . . . .
 136864291         . 1 1 . . . . .
1226405859         . 1 2 0 0 0 1 0
 816941131         . 1 3 . . . . .
 952089099         . 1 4 . . . . .
 544211495         . 1 3 . . . . .
1429125411         . 1 5 . . . . .
 477702727         . 1 3 0 0 0 0 0
  68383529  13280481 1 3 . . . . .
  71034853  91722071 1 3 . . . . .
 476495727         . 1 2 . . . . .
1088748687         . 1 1 . . . . .
1234934570         . 1 3 0 0 0 0 0
 558471085  94968195 1 1 . . . . .
 138154925  11564172 1 1 . . . . .
 952686811         . 1 4 . . . . .
 275957728         . 1 2 . . . . .
1632845931         . 1 1 . . . . .
 613676213  35671246 1 1 . . . . .
 749284531         . 1 2 . . . . .
 136569851         . 1 4 . . . . .
 476497783         . 1 1 . . . . .
1360282891         . 1 1 . . . . .
 476497783         . 1 3 . . . . .
 816975807         . 1 5 0 0 0 0 0
 204562371         . 1 3 . . . . .
1497101611         . 1 1 . . . . .
 960078602         . 1 3 0 0 0 0 0
 953241687         . 1 3 . . . . .
 817123371         . 1 1 . . . . .
 136667087         . 1 2 . . . . .
 476504571         . 1 1 . . . . .
1101076450         . 1 3 . . . . .
 545133571         . 1 1 . . . . .
1428504571         . 1 2 . . . . .
 476505247         . 1 3 . . . . .
 749470165  16277627 1 4 . . . . .
1632218287         . 1 2 . . . . .
1428017007         . 1 1 . . . . .
 953139007         . 1 3 0 0 0 0 0
 544604531         . 1 1 . . . . .
1020093171         . 1 3 . . . . .
 410131147         . 1 4 0 0 0 0 0
 163753525 118822969 1 3 . . . . .
 476131245  11205849 1 4 . . . . .
1564567135         . 1 3 . . . . .
1292182931         . 1 2 . . . . .
1428964247         . 1 1 . . . . .
 476514771         . 1 1 . . . . .
  69003687         . 1 2 . . . . .
 341338935         . 1 1 . . . . .
1158492887         . 1 1 0 0 0 0 0
 884398491         . 1 2 . . . . .
 476514779         . 1 2 . . . . .
1564605211         . 1 1 . . . . .
  95740605 118812769 1 3 . . . . .
 885993775         . 1 2 0 0 0 0 0
 340214895         . 1 5 0 0 0 0 0
1293752367         . 1 2 0 0 0 0 0
1292937731         . 1 1 . . . . .
  69062859         . 1 5 0 0 0 0 0
1428765011         . 1 2 . . . . .
 163809285 118544365 1 1 . . . . .
1633269567         . 1 5 0 0 0 0 1
  68813979         . 1 5 0 0 0 0 0
 476529727         . 1 3 . . . . .
1225584526         . 1 2 . . . . .
 749840767         . 1 1 0 0 0 0 0
 748669127         . 1 1 . . . . .
1293804731         . 1 5 0 0 0 0 0
1360196531         . 1 2 . . . . .
 545073731         . 1 5 0 0 0 0 0
 503911965 118726617 1 2 . . . . .
1224558299         . 1 4 . . . . .
 748552863         . 1 5 0 0 0 0 0
 476533127         . 1 5 0 0 0 0 0
 693727169  94549478 1 2 . . . . .
 817337577  56546289 1 2 . . . . .
1174094890         . 1 3 . . . . .
  70786653 163811504 1 4 . . . . .
 885111139         . 1 3 . . . . .
 272881967         . 1 1 . . . . .
 408391687         . 1 2 . . . . .
 273064211         . 1 3 . . . . .
 342016887         . 1 5 0 0 0 0 0
end
label values pid pid
label values sex c_sex
label def c_sex 1 "male", modify

label def yesno 0 no 1 yes 
label val unsafe? yesno 

groups wave sex unsafe?, sepby(wave) percent(wave sex)

  +---------------------------------------------------------------------------------+
  | wave    sex   unsafe1   unsafe2   unsafe3   unsafe4   unsafe5   Freq.   Percent |
  |---------------------------------------------------------------------------------|
  |    1   male        no        no        no        no        no       2    100.00 |
  |---------------------------------------------------------------------------------|
  |    2   male        no        no        no        no        no       2     66.67 |
  |    2   male        no        no        no       yes        no       1     33.33 |
  |---------------------------------------------------------------------------------|
  |    3   male        no        no        no        no        no       4    100.00 |
  |---------------------------------------------------------------------------------|
  |    4   male        no        no        no        no        no       3     75.00 |
  |    4   male        no        no        no       yes        no       1     25.00 |
  |---------------------------------------------------------------------------------|
  |    5   male        no        no        no        no        no      10     90.91 |
  |    5   male        no        no        no        no       yes       1      9.09 |
  +---------------------------------------------------------------------------------+

.
A dot or bar chart could work as well or better than a table. The data example here leads to examples that are possibly misleading. To give people a better chance of suggesting alternatives you could show the results of say

contract wave sex unsafe1 unsafe2 unsafe3

which as a dataset with no more than 80 observations could be shown comfortably here.

Do you want to see joint distributions, or just marginal distributions?

[Ana Vasconcelos]

The commands are not working. I have stata 16. I just want to have a single table where I can see how many individuals answered "yes" or "no" to the questions represented by unsafe1 unsafe 2 unsafe 3 in each wave (waves 1 - 5).
Thank you very much in advance.

[Nick Cox]

So, marginal not joint distributions are what you want? Better data example please.

[Ana Vasconcelos]

Yes, marginal distributions. I send the example of the dataset below. Thank you very much

* Example generated by -dataex-. For more info, type help dataex
clear
input long(pidp pid) byte sex float wave byte(unsafe1 unsafe2 unsafe3 unsafe4 unsafe5 unsafe6 unsafe7 unsafe8 unsafe9 unsafe10 unsafe11 unsafe96 unsafe97)
 409647647         . 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0
1634610527         . 2 1 0 0 0 0 0 0 0 0 0 0 0 1 0
 952072767         . 1 1 . . . . . . . . . . . . .
 341491247         . 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0
 748431807         . 2 1 . . . . . . . . . . . . .
 708011929 119124416 2 1 . . . . . . . . . . . . .
1360308727         . 1 1 . . . . . . . . . . . . .
1225350487         . 1 1 . . . . . . . . . . . . .
 544259091         . 1 1 . . . . . . . . . . . . .
 614078773 101104774 2 1 . . . . . . . . . . . . .
  68615407         . 1 1 . . . . . . . . . . . . .
 816091127         . 2 1 . . . . . . . . . . . . .
 272061207         . 1 1 . . . . . . . . . . . . .
 749772085  16283228 2 1 . . . . . . . . . . . . .
1360784047         . 1 1 . . . . . . . . . . . . .
 340041485  10485937 1 1 . . . . . . . . . . . . .
1225351167         . 2 1 . . . . . . . . . . . . .
 681248495         . 2 1 . . . . . . . . . . . . .
 615472765  13796682 1 1 . . . . . . . . . . . . .
1632425011         . 2 1 . . . . . . . . . . . . .
1227788364         . 1 1 . . . . . . . . . . . . .
 544743927         . 1 1 . . . . . . . . . . . . .
 885260051         . 1 1 . . . . . . . . . . . . .
 218308565  95300988 2 1 . . . . . . . . . . . . .
 748062567         . 2 1 . . . . . . . . . . . . .
 340541979         . 1 1 . . . . . . . . . . . . .
 143426362         . 1 1 . . . . . . . . . . . . .
1292517487         . 1 1 . . . . . . . . . . . . .
1564891499         . 1 1 . . . . . . . . . . . . .
  70642489  11221542 1 1 . . . . . . . . . . . . .
1496920047         . 2 1 . . . . . . . . . . . . .
 681433447         . 2 1 0 0 0 0 0 0 0 0 0 0 0 1 0
 136749375         . 1 1 . . . . . . . . . . . . .
 694091645  95574379 1 1 . . . . . . . . . . . . .
1021262771         . 2 1 . . . . . . . . . . . . .
 137010487         . 1 1 . . . . . . . . . . . . .
 681084615         . 1 1 . . . . . . . . . . . . .
 952172731         . 1 1 . . . . . . . . . . . . .
 408964247         . 2 1 . . . . . . . . . . . . .
 750696207         . 1 1 . . . . . . . . . . . . .
1501555804         . 1 1 . . . . . . . . . . . . .
 204841303         . 1 1 . . . . . . . . . . . . .
1428233247         . 2 1 . . . . . . . . . . . . .
 476830971         . 2 1 . . . . . . . . . . . . .
 218361605  95304339 1 1 . . . . . . . . . . . . .
 490342569 116780584 1 1 . . . . . . . . . . . . .
 341064889  18385869 2 1 . . . . . . . . . . . . .
 206628889  28951875 1 1 . . . . . . . . . . . . .
 681140371         . 2 1 . . . . . . . . . . . . .
 816159811         . 2 1 . . . . . . . . . . . . .
1156160487         . 1 1 . . . . . . . . . . . . .
1225981535         . 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0
  68667767         . 1 1 . . . . . . . . . . . . .
 341224007         . 2 1 . . . . . . . . . . . . .
 218377933 105285838 1 1 . . . . . . . . . . . . .
 752250084         . 2 1 . . . . . . . . . . . . .
 748291727         . 2 1 . . . . . . . . . . . . .
 163984045 119099918 1 1 . . . . . . . . . . . . .
  69326687         . 1 1 . . . . . . . . . . . . .
 163971129 119089459 2 1 . . . . . . . . . . . . .
 218398333 156018985 1 1 . . . . . . . . . . . . .
 340423647         . 1 1 . . . . . . . . . . . . .
 496855613  98485695 1 1 . . . . . . . . . . . . .
 816199931         . 2 1 . . . . . . . . . . . . .
 545355297 171552954 2 1 . . . . . . . . . . . . .
 408357695         . 1 1 . . . . . . . . . . . . .
 232159485 119261235 2 1 . . . . . . . . . . . . .
1088232567         . 1 1 . . . . . . . . . . . . .
 367605973 118569481 1 1 . . . . . . . . . . . . .
 218411249  95843639 1 1 . . . . . . . . . . . . .
 136760927         . 1 1 . . . . . . . . . . . . .
1564147567         . 2 1 . . . . . . . . . . . . .
 748571964         . 2 1 . . . . . . . . . . . . .
1157022735         . 1 1 . . . . . . . . . . . . .
1021606855         . 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0
1088362447         . 1 1 . . . . . . . . . . . . .
 750516005  14524368 1 1 . . . . . . . . . . . . .
 816707211         . 1 1 . . . . . . . . . . . . .
1565033615         . 2 1 . . . . . . . . . . . . .
1360542655         . 1 1 . . . . . . . . . . . . .
1566525531         . 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0
1088314167         . 2 1 . . . . . . . . . . . . .
    956765  17401356 1 1 . . . . . . . . . . . . .
 612021085  10197087 2 1 . . . . . . . . . . . . .
 272151651         . 2 1 . . . . . . . . . . . . .
 274239251         . 2 1 0 0 0 0 0 0 0 0 0 0 0 1 0
1156575971         . 1 1 . . . . . . . . . . . . .
1088715367         . 2 1 . . . . . . . . . . . . .
1089160087         . 1 1 . . . . . . . . . . . . .
 275781485  18503446 2 1 . . . . . . . . . . . . .
 204574611         . 1 1 . . . . . . . . . . . . .
 837186089 157347206 2 1 . . . . . . . . . . . . .
 408348851         . 1 1 . . . . . . . . . . . . .
 953094127         . 1 1 . . . . . . . . . . . . .
  69082571         . 2 1 . . . . . . . . . . . . .
1088259771         . 1 1 . . . . . . . . . . . . .
 612992815         . 2 1 . . . . . . . . . . . . .
 218479257  96353228 1 1 . . . . . . . . . . . . .
 953206331         . 2 1 . . . . . . . . . . . . .
1292750735         . 2 1 . . . . . . . . . . . . .
end
label values pid pid
label values sex c_sex
label def c_sex 1 "male", modify
label def c_sex 2 "female", modify
label values unsafe1 c_unsafe1
label def c_unsafe1 0 "not mentioned", modify
label values unsafe2 c_unsafe2
label def c_unsafe2 0 "not mentioned", modify
label values unsafe3 c_unsafe3
label def c_unsafe3 0 "not mentioned", modify
label values unsafe4 c_unsafe4
label def c_unsafe4 0 "not mentioned", modify
label values unsafe5 c_unsafe5
label def c_unsafe5 0 "not mentioned", modify
label values unsafe6 c_unsafe6
label def c_unsafe6 0 "not mentioned", modify
label values unsafe7 c_unsafe7
label def c_unsafe7 0 "not mentioned", modify
label values unsafe8 c_unsafe8
label def c_unsafe8 0 "not mentioned", modify
label values unsafe9 c_unsafe9
label def c_unsafe9 0 "not mentioned", modify
label values unsafe10 c_unsafe10
label def c_unsafe10 0 "not mentioned", modify
label values unsafe11 c_unsafe11
label def c_unsafe11 0 "not mentioned", modify
label values unsafe96 c_unsafe96
label def c_unsafe96 1 "Mentioned", modify
label values unsafe97 c_unsafe97
label def c_unsafe97 0 "not mentioned", modify

[Nick Cox]

Thanks for the new data example. This may or may not help. It's destructive, so save the dataset first if not already done.

. reshape long unsafe , i(pidp) j(which)
(j = 1 2 3 4 5 6 7 8 9 10 11 96 97)

Data                               Wide   ->   Long
-----------------------------------------------------------------------------
Number of observations              100   ->   1,300       
Number of variables                  17   ->   6           
j variable (13 values)                    ->   which
xij variables:
           unsafe1 unsafe2 ... unsafe97   ->   unsafe
-----------------------------------------------------------------------------

. 
. drop pid* 

. drop if missing(unsafe)
(1,196 observations deleted)

. 
. groups wave sex which unsafe , percent(wave sex which) sepby(wave sex which)

  +---------------------------------------------------------+
  | wave      sex   which          unsafe   Freq.   Percent |
  |---------------------------------------------------------|
  |    1     male       1   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male       2   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male       3   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male       4   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male       5   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male       6   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male       7   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male       8   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male       9   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male      10   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male      11   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1     male      96               1       5    100.00 |
  |---------------------------------------------------------|
  |    1     male      97   not mentioned       5    100.00 |
  |---------------------------------------------------------|
  |    1   female       1   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female       2   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female       3   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female       4   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female       5   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female       6   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female       7   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female       8   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female       9   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female      10   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female      11   not mentioned       3    100.00 |
  |---------------------------------------------------------|
  |    1   female      96               1       3    100.00 |
  |---------------------------------------------------------|
  |    1   female      97   not mentioned       3    100.00 |
  +---------------------------------------------------------+

[Ana Vasconcelos]

Thank you very much!