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Improving surveys with paradata : analytic uses of process information / edited by Frauke Kreuter, Joint Program in Survey Methodology, University of Maryland, Institute for Employment Research, Nuremberg, Ludwig Maximilian University, Munich.
Format
Book
Language
English
Published/Created
Hoboken, New Jersey : Wiley & Sons, [2013]
©2013
Description
xxii, 392 pages : illustrations ; 24 cm
Availability
Available Online
O'Reilly Online Learning: Academic/Public Library Edition
Ebook Central Perpetual, DDA and Subscription Titles
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Call Number
Status
Location Service
Notes
Firestone Library - Stacks
HA31.2 .I47 2013
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Details
Subject(s)
Surveys
—
Statistical methods
[Browse]
Social surveys
—
Statistical methods
[Browse]
Social sciences
—
Research
—
Statistical methods
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Related name
Kreuter, Frauke
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Series
Wiley series in survey methodology
[More in this series]
Summary note
"Paradata are measurements related to the process of collecting survey data. 'Improving Surveys with Paradata: Analytic Uses of Process Information' is the most accessible and comprehensive contribution to this up-and-coming area in survey methodology. Featuring contributions from leading experts in the field, 'Improving Surveys with Paradata: Analytic Uses of Process Information' introduces and reviews issues involved in the collection and analysis of paradata. The book presents readers with an overview of the indispensable techniques and new, innovative research on improving survey quality and total survey error. Along with several case studies, topics include: Using paradata to monitor fieldwork activity in face-to-face, telephone, and web surveys; Guiding intervention decisions during data collection; Analysis of measurement, nonresponse, and coverage error via paradata."-- Provided by publisher.
Bibliographic references
Includes bibliographical references and index.
Contents
1 Improving Surveys With Paradata: Introduction / Frauke Kreuter
2. Paradata For Nonresponse Error Investigation / Frauke Kreuter and Kristen Olson
3. Collecting Paradata For Measurement Error Evaluations / Kristen Olson and Bryan Parkhurst
4. Analyzing Paradata To Investigate Measurement Error / Ting Yan and Kristen Olson
5. Paradata For Coverage Research / Stephanie Eckman
6. Design And Management Strategies For Paradata-Driven Responsive Design: Illustrations From The 2006-2010 National Survey Of Family Growth / Nicole G. Kirgis and James M. Lepkowski
7. Using Paradata-Driven Models To Improve Contact Rates In Telephone And Face-To-Face Surveys / James Wagner
8. Using Paradata To Study Response To Within-Survey Requests / Joseph W. Sakshaug
9. Managing Data Quality Indicators With Paradata Based Statistical Quality Control Tools: The Keys To Survey Performance / Matt Jans, Robyn Sirkis and David Morgan
10. Paradata As Input To Monitoring Representativeness And Measurement Profiles: A Case Study Of The Dutch Labour Force Survey / Barry Schouten and Melanie Calinescu
11. Paradata In Web Surveys / Mario Callegaro
12. Modeling Call Record Data: Examples From Cross-Sectional And Longitudinal Surveys / Gabriele B. Durrant, Julia D'Arrigo and Gerrit Müller
13. Bayesian Penalized Spline Models For Statistical Process Monitoring Of Survey Paradata Quality Indicators / Joseph L. Schafer
14. The Quality Of Paradata: A Literature Review / Brady T. West and Jennifer Sinibaldi
15. The Effects Of Errors In Paradata On Weighting Class Adjustments: A Simulation Study / Brady T. West.
Show 12 more Contents items
ISBN
9780470905418 ((cloth))
0470905417 ((cloth))
LCCN
2013000328
OCLC
825106753
Other standard number
40022429256
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Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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Other versions
Improving surveys with paradata : analytic uses of process information / editor, Frauke Kreuter.
id
99125207996006421
Improving surveys with paradata : analytic use of process information / edited by Frauke Kreuter, Joint Program in Survey Methodology, University of Maryland, Institute for Employment Research, Nuremberg, Ludwig Maximilian University, Munich.
id
SCSB-8862260