A Closer Look at Attitude Scales with Positive and Negative Items. Response Latency Perspectives on Measurement Quality

Measurement quality in standardized surveys has been a core issue for decades in survey research. For questionnaire designers, it is common to use a mix of positive and negative worded items to measure multi-item-constructs in order to control for response effects like acquiescence bias. The paper...

Full description

Bibliographic Details
Main Authors: Jochen Mayerl, Christoph Giehl
Format: Article
Language:English
Published: European Survey Research Association 2018-12-01
Series:Survey Research Methods
Subjects:
Online Access:https://ojs.ub.uni-konstanz.de/srm/article/view/7207
id doaj-913a7f6600ef472aa07985bdb91dc805
record_format Article
spelling doaj-913a7f6600ef472aa07985bdb91dc8052020-11-24T21:54:37ZengEuropean Survey Research AssociationSurvey Research Methods1864-33612018-12-0112310.18148/srm/2018.v12i3.7207A Closer Look at Attitude Scales with Positive and Negative Items. Response Latency Perspectives on Measurement QualityJochen Mayerl0Christoph Giehl1technical university of kaiserslauterntechnical university of kaiserslauternMeasurement quality in standardized surveys has been a core issue for decades in survey research. For questionnaire designers, it is common to use a mix of positive and negative worded items to measure multi-item-constructs in order to control for response effects like acquiescence bias. The paper shows that paradata such as response latency measurement can be used to identify specific subgroups of respondents with specific types of cognitive response modes. These response modes moderate the occurrence of response effects, systematic and random measurement errors, and thus the reliability and validity of attitudinal measurement models. Therefore, adapting paradata to detect low measurement quality can be used as a tool leading to a better understanding of respondents’ cognitive processes. Data of a German CATI-survey with experimental design and measurement of response latencies are used to analyze data quality of a measurement model of attitudes towards health nutrition with mixed items. Response effects are analyzed through the experimental variation of question order of negative and positive worded items. Structural equation models are estimated in a multiple-group moderator design to test validity and reliability of the latent attitude construct. As a result, the attitude scale shows acceptable values of validity and reliability only under the condition of spontaneous answers where question order effects appear.https://ojs.ub.uni-konstanz.de/srm/article/view/7207Response LatencyParadataReversed ItemsMethod EffectsCognition in Surveys
collection DOAJ
language English
format Article
sources DOAJ
author Jochen Mayerl
Christoph Giehl
spellingShingle Jochen Mayerl
Christoph Giehl
A Closer Look at Attitude Scales with Positive and Negative Items. Response Latency Perspectives on Measurement Quality
Survey Research Methods
Response Latency
Paradata
Reversed Items
Method Effects
Cognition in Surveys
author_facet Jochen Mayerl
Christoph Giehl
author_sort Jochen Mayerl
title A Closer Look at Attitude Scales with Positive and Negative Items. Response Latency Perspectives on Measurement Quality
title_short A Closer Look at Attitude Scales with Positive and Negative Items. Response Latency Perspectives on Measurement Quality
title_full A Closer Look at Attitude Scales with Positive and Negative Items. Response Latency Perspectives on Measurement Quality
title_fullStr A Closer Look at Attitude Scales with Positive and Negative Items. Response Latency Perspectives on Measurement Quality
title_full_unstemmed A Closer Look at Attitude Scales with Positive and Negative Items. Response Latency Perspectives on Measurement Quality
title_sort closer look at attitude scales with positive and negative items. response latency perspectives on measurement quality
publisher European Survey Research Association
series Survey Research Methods
issn 1864-3361
publishDate 2018-12-01
description Measurement quality in standardized surveys has been a core issue for decades in survey research. For questionnaire designers, it is common to use a mix of positive and negative worded items to measure multi-item-constructs in order to control for response effects like acquiescence bias. The paper shows that paradata such as response latency measurement can be used to identify specific subgroups of respondents with specific types of cognitive response modes. These response modes moderate the occurrence of response effects, systematic and random measurement errors, and thus the reliability and validity of attitudinal measurement models. Therefore, adapting paradata to detect low measurement quality can be used as a tool leading to a better understanding of respondents’ cognitive processes. Data of a German CATI-survey with experimental design and measurement of response latencies are used to analyze data quality of a measurement model of attitudes towards health nutrition with mixed items. Response effects are analyzed through the experimental variation of question order of negative and positive worded items. Structural equation models are estimated in a multiple-group moderator design to test validity and reliability of the latent attitude construct. As a result, the attitude scale shows acceptable values of validity and reliability only under the condition of spontaneous answers where question order effects appear.
topic Response Latency
Paradata
Reversed Items
Method Effects
Cognition in Surveys
url https://ojs.ub.uni-konstanz.de/srm/article/view/7207
work_keys_str_mv AT jochenmayerl acloserlookatattitudescaleswithpositiveandnegativeitemsresponselatencyperspectivesonmeasurementquality
AT christophgiehl acloserlookatattitudescaleswithpositiveandnegativeitemsresponselatencyperspectivesonmeasurementquality
AT jochenmayerl closerlookatattitudescaleswithpositiveandnegativeitemsresponselatencyperspectivesonmeasurementquality
AT christophgiehl closerlookatattitudescaleswithpositiveandnegativeitemsresponselatencyperspectivesonmeasurementquality
_version_ 1725866791831339008