Handbook on Population and Housing Census Editing

1. Handbook on Populationand Housing Census Editing Department of Economic and Social Development United Nations Statistics Division Studies in Methods, Series F, No.82

2. Purpose of Handbook • No census data are ever perfect • Changes are made -- little documentation • Promote communication between subject specialists and programmers • “Cookbook” of suggestions -- presents possible resolutions • But country edit teams must decide

3. Major Elements in a Census • Preparatory work • Enumeration • Data processing -- keying, editing and tabulations • Building data bases and dissemination • Evaluation of results • Analysis of results

4. Errors in Census Process • Coverage Errors • Questionnaire Design • Enumerator/respondent errors • Coding errors • Data entry errors • Computer editing errors • Tabulation errors

5. Editing in Historical Perspective • Before computers: manual editing • With computers: Increased complexity • Automated changes • Generalized editing packages • New philosophies of editing • Personal computers • Appropriate levels of computer editing

6. Editing Team • Appropriate internal subject matter specialists • Computer Programmers • Work together as a team • Edit Specs as means of communication • Outside experts -- academicians • Outside experts -- private sector

7. WHAT CENSUS EDITING SHOULD DO • Give users measures of the quality of the data • Identify the types and sources of error, and • Provide adjusted census results

8. Sample table with & without unknowns

9. Table showing trends with unknowns

10. Basics of Census Editing • Systematic inspection and change (not always correction) • Fatal edits -- invalid or missing entries • Query edits -- inconsistencies • Must preserve the original data as much as possible • Quality enumeration more important than editing • Edit does not improve data quality -- makes more esthetic • Team must determine how far to do

11. More of Basics • Over-editing is harmful • Treatment of unknowns • Spurious changes • Determining tolerances • Learning from the edit process • Quality assurance • Costs of Editing • Imputation • Archiving

12. How Over-editing is Harmful • Timeliness • Finances • Distortion of true values • A false sense of security

13. Editing Applications • Manual versus automatic correction • Guidelines for correcting data • Validity and consistency checks • Methods of correcting and imputing data • Other editing systems

14. Manual versus Automatic Correction • Manual correction: takes a long time and very subject to error • Automatic correction: faster and consistent. • Not necessarily correct, just consistent. • Can look at many variables at the same time • Can keep an audit trail

15. Guidelines for Correcting Data • Make the fewest required changes possible to the originally collected data • Eliminate obvious inconsistencies among the entries • Systematically supply entries for erroneous or missing items by using other entries for the housing unit, person, or other persons in the household or group • When appropriate, use “not reported”

17. Validity and Consistency Checks • Top-down editing approach • Multiple variable edit • Coding considerations

18. Methods of Correcting and Imputing Data • Change to unknown • Static or “Cold Deck” imputation • Dynamic or “Hot deck” imputation

19. Hot Deck Imputation • Geographic considerations • Use of related items • Sequence of the items • Complexity of the matrices • Standardized hot decks • Size of hot decks -- too big, audit trail, too small, difficult items

20. Language Edit • If this is the head and language is missing, first look for someone else in the house with language, and assign that. • If this is the head without language, no one else has language, use neighboring head of similar characteristics to assign a best guess. • If this is someone else in the house and language is missing, assign the head’s language.

21. Language Edit: Within House

22. Language Edit: Imputed House

23. THANK YOU Everyone come to your census!