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A Permutation Test for Correlated Errors in Adjacent Questionnaire Items

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Title: A Permutation Test for Correlated Errors in Adjacent Questionnaire Items
Language: English
Authors: Hildreth, Laura A., Genschel, Ulrike, Lorenz, Frederick O., Lesser, Virginia M.
Source: Structural Equation Modeling: A Multidisciplinary Journal. 2013 20(2):226-240.
Availability: Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 15
Publication Date: 2013
Document Type: Journal Articles
Reports - Research
Descriptors: Questionnaires, Response Style (Tests), Structural Equation Models, Surveys, Correlation, Simulation, Computer Oriented Programs, Statistical Analysis
Geographic Terms: Oregon
DOI: 10.1080/10705511.2013.769390
ISSN: 1070-5511
Abstract: Response patterns are of importance to survey researchers because of the insight they provide into the thought processes respondents use to answer survey questions. In this article we propose the use of structural equation modeling to examine response patterns and develop a permutation test to quantify the likelihood of observing a specific response pattern. Of interest is a response pattern where the response to the current item is conditioned on the respondent's answer to the immediately preceding item. This pattern manifests itself in the error structure of the survey items by resulting in larger correlations of the errors for adjacent items than for nonadjacent items. We illustrate the proposed method using data from the 2002 Oregon Survey of Roads and Highways and report SAS code that can be easily modified to examine other response patterns of interest. (Contains 2 tables, 3 figures, and 1 footnote.)
Abstractor: As Provided
Number of References: 32
Entry Date: 2014
Accession Number: EJ1012557
Database: ERIC
FullText Text:
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  Data: A Permutation Test for Correlated Errors in Adjacent Questionnaire Items
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  Data: Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
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  Data: 10.1080/10705511.2013.769390
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  Data: Response patterns are of importance to survey researchers because of the insight they provide into the thought processes respondents use to answer survey questions. In this article we propose the use of structural equation modeling to examine response patterns and develop a permutation test to quantify the likelihood of observing a specific response pattern. Of interest is a response pattern where the response to the current item is conditioned on the respondent's answer to the immediately preceding item. This pattern manifests itself in the error structure of the survey items by resulting in larger correlations of the errors for adjacent items than for nonadjacent items. We illustrate the proposed method using data from the 2002 Oregon Survey of Roads and Highways and report SAS code that can be easily modified to examine other response patterns of interest. (Contains 2 tables, 3 figures, and 1 footnote.)
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