Survey Methodology
Science and survey management

by Roger TourangeauNote 1

  • Release date: June 24, 2021
More information PDF version

Abstract

It is now possible to manage surveys using statistical models and other tools that can be applied in real time. This paper focuses on three developments that reflect the attempt to take a more scientific approach to the management of survey field work: 1) the use of responsive and adaptive designs to reduce nonresponse bias, other sources of error, or costs; 2) optimal routing of interviewer travel to reduce costs; and 3) rapid feedback to interviewers to reduce measurement error. The article begins by reviewing experiments and simulation studies examining the effectiveness of responsive and adaptive designs. These studies suggest that these designs can produce modest gains in the representativeness of survey samples or modest cost savings, but can also backfire. The next section of the paper examines efforts to provide interviewers with a recommended route for their next trip to the field. The aim is to bring interviewers’ field work into closer alignment with research priorities while reducing travel time. However, a study testing this strategy found that interviewers often ignore such instructions. Then, the paper describes attempts to give rapid feedback to interviewers, based on automated recordings of their interviews. Interviewers often read questions in ways that affect respondents’ answers; correcting these problems quickly yielded marked improvements in data quality. All of the methods are efforts to replace the judgment of interviewers, field supervisors, and survey managers with statistical models and scientific findings.

Key Words: Survey management; Responsive design; Adaptive design; Optimal routing.

Table of contents

How to cite

Tourangeau, R. (2021). Science and survey management. Survey Methodology, Statistics Canada, Catalogue No. 12-001-X, Vol. 47, No. 1. Paper available at http://www.statcan.gc.ca/pub/12-001-x/2021001/article/00006-eng.htm.

Note

More information

ISSN : 1492-0921

Editorial policy

Survey Methodology publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves. All papers will be refereed. However, the authors retain full responsibility for the contents of their papers and opinions expressed are not necessarily those of the Editorial Board or of Statistics Canada.

Submission of Manuscripts

Survey Methodology is published twice a year in electronic format. Authors are invited to submit their articles in English or French in electronic form, preferably in Word to the Editor, (statcan.smj-rte.statcan@canada.ca, Statistics Canada, 150 Tunney’s Pasture Driveway, Ottawa, Ontario, Canada, K1A 0T6). For formatting instructions, please see the guidelines provided in the journal and on the web site (www.statcan.gc.ca/SurveyMethodology).

Note of appreciation

Canada owes the success of its statistical system to a long-standing partnership between Statistics Canada, the citizens of Canada, its businesses, governments and other institutions. Accurate and timely statistical information could not be produced without their continued co-operation and goodwill.

Standards of service to the public

Statistics Canada is committed to serving its clients in a prompt, reliable and courteous manner. To this end, the Agency has developed standards of service which its employees observe in serving its clients.

Copyright

Published by authority of the Minister responsible for Statistics Canada.

© Her Majesty the Queen in Right of Canada as represented by the Minister of Industry, 2021

Use of this publication is governed by the Statistics Canada Open Licence Agreement.

Catalogue No. 12-001-X

Frequency: Semi-annual

Ottawa

close


Table of contents

Abstract - Article main page
Section 1. Introduction
Section 2. Responsive and adaptive design
Section 3. Optimal routing
Section 4. Rapid CARI feedback
Section 5. Conclusions
Acknowledgements
References

close
Date modified: