Data Quality in Multi-sited Cross-Sectional and Panel Studies.

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Eric C. Jones, Research Scientist (Creator)
Arthur D. Murphy, Professor and Department Head (Creator)
The University of North Carolina at Greensboro (UNCG )
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Abstract: The authors address the issues faced while collecting survey data as part of a large multisite, multidisciplinary long-term project using interviewers rather than self-administered questionnaires in a country in which the researchers are not native. The issues pertain to the collection of high-quality data that accurately measure the variables of interest from which generalizations can be made. Three issues were prominent: potential cross-cultural variation in the validity of measures; how to manage multiple control sites and multiple study sites; and how to control for problems presented by series/panel data (i.e., the influence of prior interviews or subsequent intervening events on later interviews). The authors addressed these issues through five strategies at different points in the study. This discussion concerns the challenges and benefits of using these techniques to address the three main issues.

Additional Information

Language: English
Date: 2010
anthropology, psychology, disaster, Mexico, data quality, data collection, research methods

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