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Multiple Indicator Cluster Surveys Data Processing Workshop

Multiple Indicator Cluster Surveys Data Processing Workshop. Secondary Editing. REMEMBER AND REMIND YOUR FIELD STAFF:.

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Multiple Indicator Cluster Surveys Data Processing Workshop

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  1. MICS Data Processing Workshop Multiple Indicator Cluster SurveysData Processing Workshop 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 carefully specified editing guidelines consistently and carefully.

  3. Secondary Editing Flow Chart Backup Raw (unedited) Data File DP Supervisor Enter Corrections into Raw Data File Secondary Editing Listing DP Supervisor DP Supervisor Yes Resolve Inconsistencies on paper listing Inconsistencies? Secondary Editor No Backup Final (edited) 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 the codes for inconsistent (7, 97, 997) or missing (9, 99, 999) • 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 (almost) 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. DPT2 and Polio 2 vaccination dates differ 3. Level and grade of education inconsistent 4. Polio 3 vaccination date beforePolio 1 vaccination date

  7. Example 1: Basic Information • The Data [DOI] WM6 = 04/2009 = 1312 [DOB] WB1 = 09/1966 = 801 [Age] WB2 = 41 • The Error Message U 1003 E Age of woman (WB2=41) and her date of birth (DOB=09/1966) inconsistent [DOI=04/2009]

  8. Example 1: The Inconsistency • The Inconsistency • Age • calculated age (calcage) = 42 • reported age (WB2) = 41 • Date of birth • calculated LDOB: 1312-(12*41)-11 = 809 • calculated UDOB: 1312-(12*41) = 820 • reported DOB (using 09/1966): 801

  9. Example 1: Resolving the Inconsistency • Variables to Check • WM6, WB1, WB2, HL5(LN), HL6(LN), CM2, MA8, MA9 • Steps: 1. Check for data entry errors 2. If WM6M = WB1M, and WM2 = calcage - 1, leave unchanged 3. If WB1M and WB1Y valid, set WM2 = calcage 4. If WB1M invalid, set WB1Y = 9997 (inconsistent)

  10. Example 2: Basic Information • The Data • Polio 2: IM3C = 08/08/2008 • DPT 2: IM4B = 08/08/2009 • The Error Message U 2705 M Date of Polio 2 vaccination (08/08/2008) and date of DPT2 vaccination (08/08/2009) different • The Inconsistency • Polio and DPT shots are often given on the same date

  11. Example 2: Other Information All Polio and DPT Vaccination Dates: • Polio 1: IM3P1 = 16/06/2008 • Polio 2: IM3P2 = 08/08/2008 • Polio 3: IM3P3 = 13/09/2008 • DPT1: IM3D1 = 16/06/2008 • DPT2: IM3D2 = 08/08/2009 • DPT3: IM3D3 = 13/09/2008

  12. Example 2: Resolving the Inconsistency Steps: 1. Check for data entry errors 2. See if recording mistake was made on questionnaire • If no obvious recording mistake, leave data unchanged • We’re more interested in knowing whether the child was vaccinated—the exact timing of the event is less critical

  13. Example 3: Basic Information • The Data • ED4A = 2 { secondary } • ED4B = 11 • The Error Message • U 0090 E ED1=02: Level (ED4A=2) and grade (ED4B=11) of education inconsistent • The Inconsistency • ED4B records grade at the current level, and for this country (UK), the highest grade at the secondary level is 7

  14. Example 3: Other Information • Other Variables • Current schooling: ED6 = notappl • Schooling last year: ED8 = notappl • Highest level (woman’s questionnaire): • WB4 = 2 • WB5 = 11

  15. Example 3: Resolving the Inconsistency Steps: 1. Check for data entry errors 2. Check for interviewer errors - Does ED4B include grades passed at lower levels? 3. If available, check values of WB4 and WB5 4. If you can’t resolve inconsistency, set ED4B = 97 (inconsistent)

  16. Example 4: Basic Information • The Data • IM3P1 = 25/11/2008 • IM3P3 = 08/01/2008 • The Error Message U 2704 E Date of Polio 1 vaccination (25/11/2008) after date of Polio 3 vaccination (08/01/2008) • The Inconsistency • Polio 3 vaccination given beforePolio 1 vaccination

  17. Example 4: Other Information All Polio and DPT Vaccination Dates: • Polio 1: IM3P1 = 25/11/2008 • Polio 2: IM3P2 = 03/03/2009 • Polio 3: IM3P3 = 05/01/2008 • DPT1: IM3D1 = 25/11/2008 • DPT2: IM3D2 = 05/02/2009 • DPT3: IM3D3 = 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 edit • 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: • Describe the issue if the 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 explanation of resolution(s), list all related variables that should be examined

  22. Modifying the Editing Guidelines • Add editing guidelines for your country specific questions that were 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 apply carefully specified editing guidelines consistently and carefully.

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