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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