Project

General

Profile

Support #856

how to deal with contradictory records

Added by Min Zhang over 2 years ago. Updated over 2 years ago.

Status:
Closed
Priority:
Urgent
Assignee:
Category:
Data inconsistency
Target version:
-
Start date:
09/28/2017
Due date:
% Done:

100%

Estimated time:

Description

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

History

#1 Updated by Stephanie Auty over 2 years ago

  • Status changed from New to In Progress
  • % Done changed from 0 to 10
  • Private changed from Yes to No

Many thanks for your enquiry. The Understanding Society team is looking into it and we will get back to you as soon as we can.

Best wishes,
Stephanie Auty - Understanding Society User Support Officer

#2 Updated by Stephanie Auty over 2 years ago

  • Status changed from In Progress to Feedback
  • Assignee changed from Alita Nandi to Min Zhang
  • % Done changed from 10 to 70

Dear Min,

In the first case, it is possible that some of these respondents gained their degree through distance learning and so did not go to university. However, at least some will be a data inconsistency based on interviewer or respondent error. These two questions are not asked together in the questionnaire and there is no check implemented between them in the CAPI software.

In your second example, these differences will be due to respondent error as the youth questionnaire is self-completion. It could be that they had only smoked once and then forgotten about it by Wave 2, for example. You might decide that it’s more likely that someone would smoke and then forget than make up that they had smoked, or think that they had when they hadn’t, but you will need to decide which assumptions you are willing to make based on your research question.

Best wishes,
Stephanie Auty - Understanding Society User Support Officer

#3 Updated by Stephanie Auty over 2 years ago

  • Status changed from Feedback to Resolved
  • % Done changed from 70 to 100

#4 Updated by Stephanie Auty over 2 years ago

  • Status changed from Resolved to Closed

Also available in: Atom PDF