Survey Automation

Report and Workshop Proceedings

Oversight Committee for the Workshop on Survey Automation

Daniel L. Cork, Michael L. Cohen, Robert Groves, and William Kalsbeek, Editors

Committee on National Statistics

Division of Behavioral and Social Sciences and Education

NATIONAL RESEARCH COUNCIL
OF THE NATIONAL ACADEMIES

THE NATIONAL ACADEMIES PRESS
Washington, D.C.
www.nap.edu



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page R1
Survey Automation Report and Workshop Proceedings Oversight Committee for the Workshop on Survey Automation Daniel L. Cork, Michael L. Cohen, Robert Groves, and William Kalsbeek, Editors Committee on National Statistics Division of Behavioral and Social Sciences and Education NATIONAL RESEARCH COUNCIL OF THE NATIONAL ACADEMIES THE NATIONAL ACADEMIES PRESS Washington, D.C. www.nap.edu

OCR for page R1
THE NATIONAL ACADEMIES PRESS 500 Fifth Street, NW Washington, DC 20001 NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine. The members of the committee responsible for the report were chosen for their special competences and with regard for appropriate balance. The project that is the subject of this report was supported by contract no. SBR-9709489 between the National Academy of Sciences and the National Science Foundation. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the organizations or agencies that provided support for the project. International Standard Book Number 0-309-08930-1 (book) International Standard Book Number 0-309-51010-4 (PDF) Library of Congress Control Number: 2003106250 Additional copies of this report are available from the National Academies Press, 500 Fifth Street, NW, Washington, D.C. 20001; (202) 334-3096; Internet, http://www.nap.edu Copyright 2003 by the National Academy of Sciences. All rights reserved. Printed in the United States of America Suggested citation: National Research Council (2003). Survey Automation: Report and Workshop Proceedings. Oversight Committee for the Workshop on Survey Automation. Daniel L. Cork, Michael L. Cohen, Robert Groves, and William Kalsbeek, eds. Committee on National Statistics. Washington, DC: The National Academies Press.

OCR for page R1
THE NATIONAL ACADEMIES Advisers to the Nation on Science, Engineering, and Medicine The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science and technology and to their use for the general welfare. Upon the authority of the charter granted to it by the Congress in 1863, the Academy has a mandate that requires it to advise the federal government on scientific and technical matters. Dr. Bruce M. Alberts is president of the National Academy of Sciences. The National Academy of Engineering was established in 1964, under the charter of the National Academy of Sciences, as a parallel organization of out-standing engineers. It is autonomous in its administration and in the selection of its members, sharing with the National Academy of Sciences the responsibility for advising the federal government. The National Academy of Engineering also sponsors engineering programs aimed at meeting national needs, encourages education and research, and recognizes the superior achievements of engineers. Dr. Wm. A. Wulf is president of the National Academy of Engineering. The Institute of Medicine was established in 1970 by the National Academy of Sciences to secure the services of eminent members of appropriate professions in the examination of policy matters pertaining to the health of the public. The Institute acts under the responsibility given to the National Academy of Sciences by its congressional charter to be an adviser to the federal government and, upon its own initiative, to identify issues of medical care, research, and education. Dr. Harvey V. Fineberg is president of the Institute of Medicine. The National Research Council was organized by the National Academy of Sciences in 1916 to associate the broad community of science and technology with the Academy’s purposes of furthering knowledge and advising the federal government. Functioning in accordance with general policies determined by the Academy, the Council has become the principal operating agency of both the National Academy of Sciences and the National Academy of Engineering in providing services to the government, the public, and the scientific and engineering communities. The Council is administered jointly by both Academies and the Institute of Medicine. Dr. Bruce M. Alberts and Dr. Wm. A. Wulf are chair and vice chair, respectively, of the National Research Council. www.national-academies.org

OCR for page R1
This page in the original is blank.

OCR for page R1
OVERSIGHT COMMITTEE FOR THE WORKSHOP ON SURVEY AUTOMATION ROBERT M. GROVES(Co-Chair), Survey Research Center, University of Michigan, and Joint Program in Survey Methodology WILLIAM KALSBEEK(Co-Chair), Survey Research Unit, Department of Biostatistics, University of North Carolina MICK P. COUPER, Survey Research Center, University of Michigan, and Joint Program in Survey Methodology JOEL L. HOROWITZ, Department of Economics, Northwestern University DARYL PREGIBON, AT&T Labs—Research, Florham Park, New Jersey DANIEL L. CORK, Study Director MICHAEL L. COHEN, Senior Program Officer MICHAEL SIRI, Program Assistant

OCR for page R1
COMMITTEE ON NATIONAL STATISTICS 2003 JOHN E. ROLPH(Chair), Marshall School of Business, University of Southern California JOSEPH G. ALTONJI, Department of Economics, Yale University ROBERT M. BELL, AT&T Labs—Research, Florham Park, New Jersey LAWRENCE D. BROWN, Department of Statistics, The Wharton School, University of Pennsylvania ROBERT M. GROVES, Survey Research Center, University of Michigan, and Joint Program in Survey Methodology JOEL L. HOROWITZ, Department of Economics, Northwestern University WILLIAM KALSBEEK, Survey Research Unit, Department of Biostatistics, University of North Carolina ARLEEN LEIBOWITZ, School of Public Policy and Social Research, University of California at Los Angeles THOMAS A. LOUIS, Bloomberg School of Public Health, Johns Hopkins University VIJAYAN NAIR, Department of Statistics and Department of Industrial and Operations Engineering, University of Michigan DARYL PREGIBON, AT&T Labs—Research, Florham Park, New Jersey KENNETH PREWITT, School of Public Affairs, Columbia University NORA CATE SCHAEFFER, Department of Sociology, University of Wisconsin-Madison MATTHEW D. SHAPIRO, Department of Economics, University of Michigan ANDREW A. WHITE, Director

OCR for page R1
Preface This volume on survey automation differs in structure from other workshop reports issued by the National Academies. We have chosen to present this finished volume as the combination of two sub-reports: The proceedings of the workshop, as it occurred on April 15–16, 2002. This is a transcript of the workshop presentations, edited for basic flow and to include such presentation graphics as are essential to effectively convey the points of the presentations. A short report by the workshop’s oversight committee, containing the committee’s reactions to the proceedings of the workshop and providing its recommendations. These two reports—the report and the proceedings—are packaged together in this single volume to provide a unified discussion of the workshop material. We believe that putting the committee’s conclusions in a concise report is an effective means of communicating those results, while packaging the short report with the proceedings provides all the relevant back-up and reference material. The report is Part I of the volume; the proceedings is Part II. The surrounding sections—such as the references and acknowledgments—have been constructed such as to be applicable to both sub-reports. The text of this report contains references to particular company and trade names, including references to specific computer software packages. Such identification of specific names should not be interpreted as endorsement by the authoring committee or the National Academies, nor should it imply that the specific products are the best available for specific purposes.

OCR for page R1
This page in the original is blank.

OCR for page R1
Acknowledgments The authoring committee for the Workshop on Survey Automation extends its thanks to the many people who made the workshop possible and whose contributions helped to bridge the computer science and survey methodology communities. Our thanks first to the U.S. Census Bureau for its sponsorship of the workshop. Through a long and convoluted path from the project’s initiation to the completion of the workshop, Pat Doyle and her staff provided much useful assistance and occasional prodding, and were most receptive to questions and suggestions. The shape and content of the workshop took form rapidly after a very successful planning meeting on December 11, 2001—arranged at the request of the authoring committee—that brought selected computer scientists into the same room with the Census Bureau’s practitioners. This planning session was most useful in clarifying paths of approach to the documentation and testing problems. Pat Doyle, Janis Lea Brown, and other Census staff put together a thorough briefing within a very rapid time frame. The authoring committee is most grateful to the three computer scientists called in for the meeting—Jesse Poore, Lawrence Markosian, and James Whittaker (Florida Institute of Technology)—for their eagerness to take on a new problem in their experience. Unfortunately, other commitments precluded Whittaker from participation in the workshop itself; we nonetheless appreciate his guidance at the early stages. About the time the workshop took place, the staff was asked by the workshop’s parent committee—the Committee on National Statistics (CNSTAT)—to present a synopsis of the workshop material at the public seminar portion of CNSTAT’s regular meeting on May 8, 2002. We are very grateful to two workshop participants—Jesse Poore and Mark Pierzchala—for reprising their workshop presentations, on short notice, at the CNSTAT seminar. Travel and logistics arrangements for the workshop were deftly made by the workshop’s project assistant, Michael Siri. We also appreciate the last-minute help of Danelle Dessaint of the CNSTAT staff in arranging the participants’ dinner. Part I of this volume was reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise, in accordance

OCR for page R1
with procedures approved by the Report Review Committee of the National Research Council (NRC). The purpose of this independent review is to provide candid and critical comments that will assist the institution in making the published reports as sound as possible and to ensure that the reports meet institutional requirements for objectivity, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process. We thank the following individuals for their participation in the review of Part I of this volume: Don A. Dillman, Departments of Sociology and Rural Sociology, Washington State University; William L. Nicholls II, consultant, Alexandria, Virginia; James O’Reilly, Blaise Services at Westat, Durham, North Carolina; Stacy Prowell, Software Quality Research Laboratory, University of Tennessee; Nora Cate Schaeffer, Department of Sociology, University of Wisconsin; Elizabeth Stephenson, Institute for Social Science Research, University of California at Los Angeles; and Dave Zubrow, Software Engineering Institute, Carnegie Mellon University. Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations, nor did they see the final drafts of the reports before their release. The review of Part I was overseen by Richard Kulka, Social and Statistical Sciences, RTI International, Research Triangle Park, North Carolina. Appointed by the National Research Council, he was responsible for making certain that an independent examination of this report was carried out in accordance with institutional procedures and that all review comments were carefully considered. Responsibility for the final content of this report rests entirely with the authoring committee and the institution. Robert Groves, Co-Chair William Kalsbeek, Co-Chair Workshop on Survey Automation

OCR for page R1
Contents I Report   1     Introduction   5     Current Practice in Documentation and Testing   9     Shift from Survey Research to Software Engineering   12     Changing Survey Management Processes to Suit Software Design   14     Dealing with Complexity: Broadening the Concept of Documentation   22     Reducing Insularity   28 II Proceedings   33     Opening Remarks   35     What Makes the CAI Testing and Documentation Problems So Hard to Solve? Pat Doyle   36     Software Engineering—The Way to Be. Jesse Poore   63     Automation and Federal Statistical Surveys. Bob Groves   78     Understanding the Documentation Problem for Complex Census Bureau Computer Assisted Questionnaires. Thomas Piazza   83     The TADEQ Project: Documentation of Electronic Questionnaires. Jelke Bethlehem   97     Computer Science Approaches: Visualization Tools and Software Metrics. Thomas McCabe   116     Model-Based Testing in Survey Automation. Harry Robinson   137     Quality Right from the Start: The Methodology of Building Testing into the Product. Robert Smith   153     Interactive Survey Development: An Integrated View. Lawrence Markosian   164     Practitioner Needs and Reactions to Computer Science Approaches. Mark Pierzchala   174     Web-Based Data Collection. Roger Tourangeau   183     Interface of Survey Methods with Geographic Information Systems. Sarah Nusser   198     Prospects for Survey Data Collection Using Pen-Based Computers. Jay Levinsohn and Martin Meyer   211

OCR for page R1
    Panel Discussion: How Can Computer Science and Survey Methodology Best Interact in the Future?   226 Workshop Information   247     Agenda   247     List of Workshop Participants and Attendees   249 Bibliography   251 Biographical Sketches of Workshop Participants and Staff   253

OCR for page R1
List of Figures I-1   Example of paper-and-pencil-style questionnaire, as seen by an interviewer.   6 I-2   Example of questionnaire item flow patterns in a CAI instrument   7 I-3   Prototype product line architecture for a CAPI process.   16 I-4   Effect on mathematical complexity of a small change in code.   26 II-1   One-page excerpt (out of 63) from the core questionnaire document, Wave 3 of the Survey of Income and Program Participation (SIPP), 1993 Panel.   38 II-2   General structure of a product line architecture.   66 II-3   Schematic model of a successful software environment.   69 II-4   Conjectured multipliers on cost of correcting errors at different phases of a softwaredesignproject.   74 II-5   Item ME16 from Instrument Document (IDOC) for Wave 6 of the Survey of IncomeandProgramParticipation(SIPP).   87 II-6   “More Information About This Item” View of Item ME16 from Instrument Document (IDOC) for Wave 6 of the Survey of Income and Program Participation(SIPP).   88 II-7   Portion of a sample questionnaire, as it might be represented on paper.   99 II-8   Portion of a sample questionnaire, as it might be represented in CASES.   100 II-9   Portion of a sample questionnaire, as it might be represented in Blaise.   102 II-10   Hypothetical routing graph of a questionnaire.   103 II-11   Sample question, as coded in the Questionnaire Definition Language used in the TADEQ project.   106 II-12   Sample route instruction, as coded in the Questionnaire Definition Language (QDL) used in the TADEQ project.   107 II-13   Screen shot of TADEQ applied to a sample questionnaire, with some sub-questionnaires unfolded.   109 II-14   Screen shot of some route statistics generated by TADEQ for a sample questionnaire.   111 II-15   Simple C algorithm with flow graph.   122 II-16   More complicated C algorithm with flow graph.   123 II-17   Schematic diagram of error-prone algorithm.   125 II-18   Four sources of unstructured logic in software programs.   127 II-19   Choice A in software metrics quiz.   129 II-20   Choice B in software metrics quiz.   130 II-21   Example of large change in complexity that can be introduced by a single change in a software module.   131 II-22   Simple survey example.   141 II-23   Operational states of Windows clock application, viewed as a flow graph and a model.   142 II-24   Example of static design for a Web questionnaire.   190 II-25   Humanizing touches in a Web questionnaire interface.   191 II-26   Web instrument with human face added to personalize the instrument.   193

OCR for page R1
List of Tables II-1   Areas of Testing Within Computer-Assisted Survey Instruments   175 II-2   Response Rates from Explicit Mode Comparison Studies (List-Based Samples)   187