Understanding Society User Support

Dear Understanding Society team,

I am writing to seek your suggestions about contradictory data.

The first example is in the same wave. I ran cross-tabulation between a_qfhigh (highest qualification ever achieved) and a_fenow (age when leaving school / never went to college or university). I assume that the respondents who attained university degree would not be found in the category "never went to college or university" in the variable a_fenow. However, this is not the case.

.  tab a_qfhigh a_fenow if a_dvage>=25

                      |                   still in further education  
highest qualification |   missing  inapplica  don't kno  write in   never wen  at colleg |     Total
----------------------+------------------------------------------------------------------+----------
              missing |         1         17          0          0          0          0 |        18 
              refused |         0          3          0          2          1          0 |         6 
           don't know |         0         18          7         19         38          2 |        84 
university higher deg |         0         16          3      3,805         53        236 |     4,113 
1st degree level inc  |         0         14          3      5,458        203        296 |     5,974 
diploma in higher edu |         0          4          2      2,089        440        142 |     2,677 
teaching qualificatio |         0          0          2        574        107         23 |       706 
nursing or other medi |         0          1          2        556        335         37 |       931 
              a level |         0         11          3      1,443      1,156        152 |     2,765 
  welsh baccalaureate |         0          0          0          0          2          0 |         2 
international baccala |         0          1          0         26         10          5 |        42 
             as level |         0          1          1        104         75         13 |       194 
higher grade/advanced |         0          1          0        175        173         17 |       366 
certificate of sixth  |         0          0          0         60         49          6 |       115 
         gcse/o level |         0         18         10      3,198      5,037        262 |     8,525 
                  cse |         0          1          1        529      1,360         41 |     1,932 
standard/ordinary (o) |         0          1          0        183        430         21 |       635 
other school (inc. sc |         0          7          0        355        967         35 |     1,364 
    none of the above |         1        392         16      1,676     10,915        287 |    13,287 
----------------------+------------------------------------------------------------------+----------
                Total |         2        506         50     20,252     21,351      1,575 |    43,736 

The category that is shown as "never wen" is actually "never went to college/university".

As can be seen from the above table. there are 203+53 respondents who had university degrees, yet reported that they never went to university.

The second example is related to cross-wave youth data. I assume that if a respondent who reported yes to "ever smoked cigarettes" in wave 1 would not say no to the same question in wave 2. However, this is what I got:

  tab  a_ypevrsmo  b_ypevrsmo 

  ever smoke |
  cigarettes |   ever smoke cigarettes at all
      at all |   missing        yes         no |     Total
-------------+---------------------------------+----------
     missing |         0          1         15 |        16 
         yes |         2         74         39 |       115 
          no |        27        209      2,416 |     2,652 
-------------+---------------------------------+----------
       Total |        29        284      2,470 |     2,783 

39 respondents who said that he/she has ever smoked in wave 1 said never smoked in wave 2.

This is getting more complicated when I link wave 1-6 together.

I understand that these are measurement errors/recall errors. I could have simply recoded these contradictory records as missing. But the numbers of these recodes may seem trivial but as they add up over waves, they are not small numbers. I am not sure what I am supposed to deal with them.

Many thanks for your time,

Regards,
Min