Transitioning a Survey to Self-Administration using Adaptive, Responsive, and Tailored (ART) Design Principles and Data Visualization
Murphy Joe (),
Biemer Paul () and
Berry Chip ()
Additional contact information
Murphy Joe: RTI International, 230 W Monroe St., Suite 2100, Chicago, IL, U.S.A, 60606.
Biemer Paul: RTI International, 3040 East Cornwallis Road, Post Office Box 12194, Research Triangle Park, NC 27709-2194 U.S.A.
Berry Chip: U.S. Energy Information Administration; 1000 Independence Ave., SW, Washington, DC20585, U.S.A.
Journal of Official Statistics, 2018, vol. 34, issue 3, 625-648
Abstract:
This article discusses the critical and complex design decisions associated with transitioning an interviewer-administered survey to a self-administered, postal, web/paper survey. Our approach embeds adaptive, responsive, and tailored (ART) design principles and data visualization during a multi-phased data collection operation to project the outcomes of each phase in preparation for subsequent phases. This requires rapid decision making based upon experimental results using a data visualization system to monitor critical-to-quality (CTQ) metrics and facilitate projections of outcomes from the current phase of data collection to inform the design of the subsequent phase. We describe the objectives of the overall design, the features designed to address these objectives, components of the visual adaptive total design (ATD) system for monitoring quality components and relative costs in real time, and examples of the visualization elements and functionalities that were used in one case study. We also discuss subsequent initiatives to develop an interactive version of the monitoring tool and applications for other studies, including those employing adaptive, responsive, and tailored (ART) designs. Our case study is a series of pilot studies conducted for the Residential Energy Consumption Survey (RECS), sponsored by the U.S. Energy Information Administration (EIA).
Keywords: Responsive design; adaptive design; monitoring; data collection; visualization (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:34:y:2018:i:3:p:625-648:n:3
DOI: 10.2478/jos-2018-0030
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