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MICS DATA PROCESSING

MICS DATA PROCESSING

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MICS DATA PROCESSING

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  1. MICS DATA PROCESSING Data Entry 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. Timing of Editing • Before data entry • Interviewer • Field editor • Office editor • During data entry • Date entry operator (with training and supervision) • After data entry • Secondary editor

  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. 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?

  7. A Simple Example • The number of eligible women (HH12) can’t be larger than the number of household members (HH11) Q1. Should we check for this inconsistency during data entry? Q2. Should it be resolved during data entry? Q3. What should the editing guidelines say?

  8. How Do We Handle the Inconsistency? A1. Yes, we should check: PROC HH12 if HH12 > HH11 then errmsg(0015); reenter endif; A2. Yes, it must be resolved; both variables structurally important • HH11 controls entries in household listing • HH12 controls number of women’s questionnaires

  9. How is the Inconsistency Resolved? A3. Data entry operator: • check for data entry errors • correct any that are found • if no data entry error found • count number of household members in household listing • count number of eligible women in household listing • correct HH11 and/or HH12 based on counts

  10. A Complex Example • A woman’s age (WM9) and date of birth (WM8M and WM8Y) must be consistent Q1. Should we check for this inconsistency during data entry? Q2. Should it be resolved during data entry? Q3. What should the editing guidelines say?

  11. How Does One Handle the Inconsistency? A1. Yes, we should check A2. No, inconsistency need not be resolved • while age and DOB are both critically important, this inconsistency is to complex and time consuming for data entry A3. Correct data entry errors only • This inconsistency will be resolved during secondary editing

  12. Contents of the Editing Guidelines • Message number, type and text • An explanation of the problem • Suggestions for correction or recommendation to make no changes

  13. Error Message Numbers • Error message numbers have 4 positions • position 1: questionnaire type • 0 = HH, 1 = WM, 2 = UF • position 2: module • sequential order of module inside questionnaire type • positions 3-4: unique ID within questionnaire type and module • Some exceptions to the rules

  14. Code Timing Status D Data entry Should be corrected W Data entry Check for keying errors E Secondary editing Probably needs correction M Secondary editing Unusual cases; may need correcting Types of Error Message

  15. 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

  16. 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

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

  18. 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.