MICS DATA PROCESSING

1. MICS DATA PROCESSING Secondary Editing

2. REMEMBER AND REMIND YOUR FIELD STAFF: • The best place to correct data is in the field where the respondent is available to resolve inconsistencies. Once the questionnaires reach the office, the best you can do is to apply consistently fully and carefully specified editing guidelines.

3. Secondary Editing Flow Chart Backup Raw Data File DP Supervisor Correct Raw Data File Secondary Editing DP Supervisor DP Supervisor Yes Resolve Inconsistencies Inconsistencies? Secondary Editor No Backup Final Data File DP Supervisor

4. General Rules for Resolving Inconsistencies • Review all pertinent responses in the questionnaire(s). • For skips check responses preceding and following. • Refer to the editing guidelines • Do not make up an answer - if necessary, use codes for inconsistent or missing • Change the fewest pieces of information • Leave the inconsistency without correction and document the inconsistency for users

5. Data Editing Philosophy • Field Editing • Interviewer or field editor • Using field editing manual can be fully corrected • Office Editing - Use editing guidelines • Office editor • ID and structure errors only • DE personnel • Check for data entry errors; resolve only structural inconsistencies • Secondary editor • Investigate and resolve (sometimes by taking no action) all inconsistencies

6. Four Examples 1. Woman’s age and date of birth inconsistent 2. Dates of DPT1 and Polio1 vaccinations different 3. Level of education is inconsistent 4. Date of Polio 3 vaccination before date of polio 1 vaccination

7. Example 1: Basic Information • The Data • WM6 = 04/2005 = 1264 • WM8 = 09/1962 = 753 • WM9 = 41 • The Error Message U 1003 E Age of woman (WM9=41) and her date of birth (DOB=09/1962) inconsistent [DOI=04/2005]

8. Example 1: The Inconsistency • The Inconsistency • Age • calculated age (calcage) = 42 • reported age (WM9) = 41 • Date of birth • calculated LDOB: 1264 - (12*41) - 11 = 761 • calculated UDOB: 1264 - (12*41) = 772 • reported DOB: 753

9. Example 1: Resolving the Inconsistency • Variables to Check • WM6, WM8, WM9, HL5(LN), CM2, MA6 • Steps 1. Check for data entry errors 2. If WM6M = WM8M, and WM9 = calcage - 1, leave unchanged 3. If WM8M and WM8Y valid, set WM9 = calcage 4. If WM8M invalid, set WM8Y = 9997 (inconsistent).

10. Example 2: The Problem • The Data • Polio 2: IM3C = 08/08/2003 • DPT2: IM4B = 08/08/2004 • The Error Message U 2705 M Date of Polio 2 vaccination (08/08/2003) and date of DPT2 vaccination (08/08/2004) different • The Inconsistency • polio and DPT shots are often given on the same date

11. Example 2: Other Information • Vaccination dates • Polio 1: IM3B = 16/06/2003 • Polio 2: IM3C = 08/08/2003 • Polio 3: IM3D = 13/09/2003 • DPT1: IM4A = 16/06/2003 • DPT2: IM4B = 08/08/2004 • DPT3: IM4C = 13/09/2003

12. Example 2: Resolving the Inconsistency • Steps 1. Check for data entry errors 2. See if recording mistake was made on questionnaire 3. If no obvious recording mistake, leave data unchanged.

13. Example 3: Basic Information • The Data • ED3A = 2 { secondary } • ED3B = 11 • The Error Message • U 0090 E ED1=02: Level (ED3A=2) and grade (ED3B=11) of education inconsistent • The Inconsistency • ED3B records grade at the current level, and for this country (UK), the highest secondary grade is 7.

14. Example 3: Other Information • Other Variables • Current schooling: ED6 = notappl • Schooling last year: ED8 = notappl • Highest level (woman’s questionnaire): • WM11 = 2 • WM12 = 11

15. Example 3: Resolving the Inconsistency • Steps 1. Check for data entry errors 2. Check for interviewer errors a. Does ED3B include grades passed at lower levels? 3. If available, check values of WM11 and WM12 4. If you can’t resolve inconsistency, set ED3B = 97 (inconsistent).

16. Example 4: The Problem • The Data • IM3B = 25/11/2003 • IM3D = 08/01/2003 • The Error Message U 2704 E Date of Polio 1 vaccination (25/11/2003) after date of Polio 3 vaccination (08/01/2003) • The Inconsistency • polio 3 vaccination given after polio 1 vaccination

17. Example 4: Other Information • Vaccination dates • Polio 1: IM3B = 25/11/2003 • Polio 2: IM3C = 03/03/2004 • Polio 3: IM3D = 05/01/2003 • DPT1: IM4A = 25/11/2003 • DPT2: IM4B = 05/02/2004 • DPT3: IM4C = notappl/notappl/notappl

18. Example 4: Resolving the Inconsistency • Steps 1. Check for data entry errors 2. See if recording mistake was made on questionnaire 3. If no obvious recording mistake, set day, month and year of most inconsistent date to 97, 97 and 9997 respectively

19. Adding an Edit • Add logic to the data entry application • Add message text to the message file • Add message to the editing guidelines

20. Defining the Editing Specifications • Carefully review the questionnaire • Define the edits • What is the possible inconsistency? • How should the inconsistency be handled during data entry? • How should the inconsistency be handled during secondary editing?

21. Editing Guidelines • For each inconsistency: • explain its nature if error message doesn’t make it clear • explain how to handle the inconsistency during data entry (if applicable) • explain how to handle the inconsistency during secondary editing (if applicable) • in resolution explanations, list all related variables that should be examined

22. Modifying the Editing Guidelines • Add editing guidelines for your country specific questions added to the MICS questionnaire • Modify the standard guidelines only after careful consideration by subject specialists • Document any changes to the standard guidelines • Ensure that all processing staff use the manual and apply it consistently

23. REMEMBER AND REMIND YOUR FIELD STAFF: • The best place to correct data is in the field where the respondent is available to resolve inconsistencies. Once the questionnaires reach the office, the best you can do is to consistently apply fully and carefully specified editing guidelines.