doubt on longitudinal dataset - xtdescribe

[Ana Vasconcelos]

Hello,

I have a longitudinal dataset with 5 waves. I used the command xtdescribe and I found out that have a total of 66689 individuals. Then I tried to find the number of individuals by sex (xtdescribe if sex==1 and xtdescribe if sex==2) .
the results were that I have a total of 31341 males and 35381 females. When I add these values the result was 66723 (and not 66689). I inspect the variable sex and I only have two missing observations. Can you please help me with an explanation for this? 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
22445 10127798 2
22445 10127798 2
22445 10127798 2
22445 10127798 2
29925 10192697 2
29925 10192697 2
29925 10192697 2
76165 10689869 2
76165 10689869 2
76165 10689869 2
223725 11926929 1
280165 12430439 2
280165 12430439 2
280165 12430439 2
280165 12430439 2
280165 12430439 2
333205 12908843 2
333205 12908843 2
333205 12908843 2
387605 13361163 2
387605 13361163 2
469205 13857142 2
469205 13857142 2
541285 14396769 1
541285 14396769 1
541965 14396793 2
599765 14757249 2
599765 14757249 2
599765 14757249 2
665045 15270041 1
665045 15270041 1
665045 15270041 1
732365 15752658 1
732365 15752658 1
760925 16095227 1
813285 16441141 1
813285 16441141 1
850005 16714296 1
956765 17401356 1
987365 17624592 2
1558565 36791768 2
1587125 17870879 2
1587125 17870879 2
1587125 17870879 2
1697285 42526507 1
1731965 45754268 1
1833965 50832336 1
1833965 50832336 1
1833965 50832336 1
1833965 50832336 1
2067205 65313828 1
2270525 76446336 2
2270525 76446336 2
2292285 77065891 1
2297045 77185978 1
2626845 93565895 1
2670365 94533008 2
2853965 96577029 2
2853965 96577029 2
2853965 96577029 2
2888645 96949503 2
2888645 96949503 2
2932845 97515191 1
3229325 106197851 2
3424485 113800185 2
3565925 118692798 2
3568645 118692895 1
3587685 118781707 1
3587685 118781707 1
3663845 119065835 1
3663845 119065835 1
3663845 119065835 1
3667245 119074613 2
3667245 119074613 2
3667245 119074613 2
3667245 119074613 2
3705325 119277506 2
3705325 119277506 2
3705325 119277506 2
3705325 119277506 2
3705325 119277506 2
3914085 127440488 2
3914765 127440518 1
3915445 127440534 2
3916125 127440569 2
4091565 135447429 1
4091565 135447429 1
4091565 135447429 1
4192205 141158735 2
4454005 154358304 1
4454005 154358304 1
4454005 154358304 1
4454005 154358304 1
4454005 154358304 1
4473725 154588539 1
4473725 154588539 1
4473725 154588539 1
4562125 159615704 1
4626045 164246088 1
4626045 164246088 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
[/CODE]

[Ana Vasconcelos]

Continuing last question: I send again the example of the dataset with an additional variable: wave
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
  22445  10127798 2 2
  22445  10127798 2 3
  22445  10127798 2 4
  22445  10127798 2 5
  29925  10192697 2 3
  29925  10192697 2 4
  29925  10192697 2 5
  76165  10689869 2 3
  76165  10689869 2 4
  76165  10689869 2 5
 223725  11926929 1 3
 280165  12430439 2 1
 280165  12430439 2 2
 280165  12430439 2 3
 280165  12430439 2 4
 280165  12430439 2 5
 333205  12908843 2 3
 333205  12908843 2 4
 333205  12908843 2 5
 387605  13361163 2 2
 387605  13361163 2 3
 469205  13857142 2 4
 469205  13857142 2 5
 541285  14396769 1 1
 541285  14396769 1 2
 541965  14396793 2 1
 599765  14757249 2 2
 599765  14757249 2 4
 599765  14757249 2 5
 665045  15270041 1 1
 665045  15270041 1 2
 665045  15270041 1 5
 732365  15752658 1 4
 732365  15752658 1 5
 760925  16095227 1 5
 813285  16441141 1 2
 813285  16441141 1 3
 850005  16714296 1 3
 956765  17401356 1 1
 987365  17624592 2 1
1558565  36791768 2 1
1587125  17870879 2 3
1587125  17870879 2 4
1587125  17870879 2 5
1697285  42526507 1 4
1731965  45754268 1 2
1833965  50832336 1 1
1833965  50832336 1 2
1833965  50832336 1 3
1833965  50832336 1 4
2067205  65313828 1 3
2270525  76446336 2 3
2270525  76446336 2 4
2292285  77065891 1 1
2297045  77185978 1 2
2626845  93565895 1 4
2670365  94533008 2 1
2853965  96577029 2 1
2853965  96577029 2 2
2853965  96577029 2 3
2888645  96949503 2 1
2888645  96949503 2 4
2932845  97515191 1 1
3229325 106197851 2 5
3424485 113800185 2 5
3565925 118692798 2 2
3568645 118692895 1 3
3587685 118781707 1 3
3587685 118781707 1 4
3663845 119065835 1 2
3663845 119065835 1 3
3663845 119065835 1 4
3667245 119074613 2 2
3667245 119074613 2 3
3667245 119074613 2 4
3667245 119074613 2 5
3705325 119277506 2 1
3705325 119277506 2 2
3705325 119277506 2 3
3705325 119277506 2 4
3705325 119277506 2 5
3914085 127440488 2 5
3914765 127440518 1 5
3915445 127440534 2 1
3916125 127440569 2 5
4091565 135447429 1 1
4091565 135447429 1 2
4091565 135447429 1 3
4192205 141158735 2 1
4454005 154358304 1 1
4454005 154358304 1 2
4454005 154358304 1 3
4454005 154358304 1 4
4454005 154358304 1 5
4473725 154588539 1 1
4473725 154588539 1 2
4473725 154588539 1 3
4562125 159615704 1 1
4626045 164246088 1 1
4626045 164246088 1 2
end
label values pid pid
label values sex c_sex
label def c_sex 1 "male", modify
label def c_sex 2 "female", modify

[Carlo Lazzaro]

Ana:
I cannot replicate your problem:

. xtdescribe

    pidp:  22445, 29925, ..., 4626045                        n =         50
    wave:  1, 2, ..., 5                                      T =          5
           Delta(wave) = 1 unit
           Span(wave)  = 5 periods
           (pidp*wave uniquely identifies each observation)

Distribution of T_i:   min      5%     25%       50%       75%     95%     max
                         1       1       1         2         3       5       5

     Freq.  Percent    Cum. |  Pattern
 ---------------------------+---------
       10     20.00   20.00 |  1....
        6     12.00   32.00 |  ....1
        4      8.00   40.00 |  ..1..
        4      8.00   48.00 |  ..111
        3      6.00   54.00 |  .1...
        3      6.00   60.00 |  111..
        3      6.00   66.00 |  11111
        2      4.00   70.00 |  ...1.
        2      4.00   74.00 |  ...11
       13     26.00  100.00 | (other patterns)
 ---------------------------+---------
       50    100.00         |  XXXXX

. xtdescribe if sex==1

    pidp:  223725, 541285, ..., 4626045                      n =         25
    wave:  1, 2, ..., 5                                      T =          5
           Delta(wave) = 1 unit
           Span(wave)  = 5 periods
           (pidp*wave uniquely identifies each observation)

Distribution of T_i:   min      5%     25%       50%       75%     95%     max
                         1       1       1         1         2       4       5

     Freq.  Percent    Cum. |  Pattern
 ---------------------------+---------
        4     16.00   16.00 |  ..1..
        4     16.00   32.00 |  1....
        2      8.00   40.00 |  ....1
        2      8.00   48.00 |  ...1.
        2      8.00   56.00 |  .1...
        2      8.00   64.00 |  11...
        2      8.00   72.00 |  111..
        1      4.00   76.00 |  ...11
        1      4.00   80.00 |  ..11.
        5     20.00  100.00 | (other patterns)
 ---------------------------+---------
       25    100.00         |  XXXXX

. xtdescribe if sex==2

    pidp:  22445, 29925, ..., 4192205                        n =         25
    wave:  1, 2, ..., 5                                      T =          5
           Delta(wave) = 1 unit
           Span(wave)  = 5 periods
           (pidp*wave uniquely identifies each observation)

Distribution of T_i:   min      5%     25%       50%       75%     95%     max
                         1       1       1         2         3       5       5

     Freq.  Percent    Cum. |  Pattern
 ---------------------------+---------
        6     24.00   24.00 |  1....
        4     16.00   40.00 |  ....1
        4     16.00   56.00 |  ..111
        2      8.00   64.00 |  .1111
        2      8.00   72.00 |  11111
        1      4.00   76.00 |  ...11
        1      4.00   80.00 |  ..11.
        1      4.00   84.00 |  .1...
        1      4.00   88.00 |  .1.11
        3     12.00  100.00 | (other patterns)
 ---------------------------+---------
       25    100.00         |  XXXXX

.