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Survey work

Maria Isabel Beltran. Survey work . Type of data. For evaluation purposes: Administrative data Surveys  our focus, we can complement with other sources of information Household Plot Associations Community Census and other country surveys. Data collection: Who does it?.

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Survey work

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  1. Maria Isabel Beltran Survey work

  2. Type of data • For evaluation purposes: • Administrative data • Surveys  our focus, we can complement with other sources of information • Household • Plot • Associations • Community • Census and other country surveys

  3. Data collection: Who does it? • Who collects the data? 2 main cases: • The ministry • Hiring of enumerators? Who are they going to be? • People inside the project have incentives to present a better or worse picture for their areas • A lot of effort to follow the process • An agency (statistical office or private firm) • OK, this is the type of work they do, but STILL A LOT OF EFFORT is needed to ensure quality (TORs, sample, questionnaire, training, supervision) 3

  4. Data collection • Questionnaire design • Training • Pilot test (and re-training) • Field work • Supervision • Data entry & data cleaning 4

  5. Data collection: Questionnaire • Who defines it? YOU (the IE team, not the firm) • Purpose of survey? Define: respondents, indicators, level, modules. Time & quantity trade off • Internal consistency • Omission of key issues & skip patterns • Clear and explicit questions for all circumstances • Avoid open questions (pre-code) / recall period • Respondent burden, sensitive issues last 5

  6. Data collection: Training & Pilot Test • Often underestimated part of the process. • Training  reduce variability in data collection • Pilot ensures the questionnaire is collecting all information needed to answer questions, all correct information, flows and logic of the questionnaire. • Test the instruments cover all conceivable situations • Involve the enumerators in the project  the importance of the data collected.

  7. Training…

  8. Data collection: Field Work • Almost always, it is better if organized in groups of enumerators (2-3) • Time Vs. quality • Have a clear field work plan and division of responsibilities among the group • Daily targets • Gambia:

  9. Data collection: Supervision • Supervision protocol, 1 per 2 teams? • Have a supervision strategy: 10% of the sample, 100% ? Only non valid responses? • Use an independent firm or team; that has received the training • Supervise the supervisors 9

  10. Data collection: Data Entry and Clean-up • No need to wait for data collection to finish to start data entry. Make corrections while the data is still being collected. (Missing values, inaccuracies) • Integrated concurrent data entry Vs. Concurrent Centralized data entry Vs. Computer assisted interviews • Data entry: ONE TIME NOT ENOUGH double entry at the same time, one after the other, one with supervision, … etc • If not planned… data cleaning = long & frustrating • Data is lost, quality decreases (decisions not documented)

  11. Data collection: example from India • Integrate the data collection and data entry. • Timely data • Feedback on field work on real time • Early detection of errors (like lack of uniform criteria) • The Medical Advice, Quality and Absenteeism in Rural India  project of the Center for Policy Research, New Delhi

  12. The Medical Advice, Quality and Absenteeism in Rural India • 3 separate firms: data collection, supervision, data entry • Define all possible error per questions and program them

  13. The Medical Advice, Quality and Absenteeism in Rural India

  14. Useful Data • Relevant data • Reliable data • Data that is ready when needed… ON TIME, to answer operational and policy questions. Need to have staff dedicated to the project in all phases (design, preparation, implementation, dataset documentation & validation) field coordinator.

  15. Thank You

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