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Predicting Test-Retest Reliability from Behavior Coding

By Hess, Jennifer C.

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Book Id: WPLBN0000579747
Format Type: PDF eBook
File Size: 77,578 KB.
Reproduction Date: 2005
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Title: Predicting Test-Retest Reliability from Behavior Coding  
Author: Hess, Jennifer C.
Volume:
Language: English
Subject: Government publications, Census., Census report
Collections: U.S. Census Bureau Collection
Historic
Publication Date:
Publisher: U.S. Census Bureau Department

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Hess, J. C. (n.d.). Predicting Test-Retest Reliability from Behavior Coding. Retrieved from http://hawaiilibrary.net/


Description
Statistical Reference Document

Excerpt
Excerpt: In attempting to move questionnaire design from art to science, researchers use different evaluation techniques to help determine how well questions are working. Techniques such as behavior coding, respondent debriefing, interviewer debriefing, cognitive interviewing, and nonresponse analysis all provide information to help the questionnaire designer assess whether respondents understand questions as intended and whether they are able to provide adequate answers to them. In 1994, Presser and Blair evaluated some of these methods, concluding that behavior coding provided more reliable diagnoses of question difficulties than conventional pretests involving a small number of interviewers followed by an interviewer debriefing. However, with the possible exception of some types of respondent debriefing questions, these techniques do not actually measure question reliability. Reliability data, such as those that could be obtained in a test-retest experiment (reinterview), are rarely collected as part of pretest activities because they are time-consuming, labor intensive and very costly to collect of course, the goal of good questionnaire design is to produce reliable and valid information, not simply questions that are easy for respondents to answer. But it is assumed that questions that pass the screen of the questionnaire evaluation techniques described above are also more likely to produce data that are reliable and valid.

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