Minimise data collection errors and prevent unacceptable field practices for empirically sound conclusions.

Develop a sophisticated measurement and monitoring system for pre, during, and post data collection stage to minimise survey attrition, data errors, and inconsistencies.

  • Conduct review and feedback sessions to understand technical misunderstanding and misentries by survey staff. 

  • Perform customised and real-time data quality and monitoring protocols (backchecks, GPS services) to make sure data integrity and other quality standards are maintained.

  • Perform random spot-checks and re-visits or re-interviewing a sample of respondents.

  • Develop data processing systems to clean and organise incoming survey data providing clients with well-documented data sets.

  • Documentation includes minimising inconsistencies, basic frequency counts for survey variables, outliers removed, and correctly labelled survey options and variables.

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