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Measuring Extreme Response Style

Bibliographic Data

ID7363030
AuthorsEric A Greenleaf, Eric Greenleaf (corresponding author)
Year1992
Volume56
Issue3
Pages328-328
Publication date1992-01-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenuePublic Opinion Quarterly (JOURNAL)
Journal identifiersISSN: 0033-362X • E-ISSN: 1537-5331
PublisherOxford University Press (OUP) (PUBLISHER)
DOI10.1086/269326
OpenAlexW2073635657
LanguageEN
Citations received85
References cited11

Research on extreme response style (ERS) in rating scale responses has been characterized by conflicting findings and little agreement over how to assemble and validate ERS measures. This article proposes that, when ERS is defined as a proportion of extreme responses, an ERS measure will be more accurate if the items are uncorrelated and have equal extreme response proportions. Furthermore, appropriate stochastic models should be used to assess the internal reliability and convergent validity of these measures. An ERS measure is created and validated with this method, using items from a survey administered in 1975 and 1987 to large samples of U.S. adults serving on a consumer panel. We find that ERS is stable over a lengthy survey compared to a benchmark stability for a "perfect" measure. Furthermore, the distribution of ERS over this population is stable over time. Respondents' ERS is related to their age, education level, and household income but not to their gender

Cartography · Data mining · Econometrics · Geography · Machine learning · Measure (data warehouse · Population · Reliability (semiconductor · Scale (ratio · Sociology · Stability (learning theory · Statistics · Uncorrelated · Computer Science · Consumer Behavior in Brand Consumption and Identification · Consumer Retail Behavior Studies · Demography · Mathematics · Psychology · Social Psychology

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Unique citing works85
Citations per year2,74
Citation span1995 - 2026 (32)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 85

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