Guidelines for choosing between multi-item and single-item scales for construct measurement: a predictive validity perspective |
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Authors: | Adamantios Diamantopoulos Marko Sarstedt Christoph Fuchs Petra Wilczynski Sebastian Kaiser |
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Institution: | (1) Department of Business Studies, University of Vienna, Bruenner Strasse 72, 1210 Vienna, Austria;(2) Institute for Market-based Management, Ludwig-Maximilians-University Munich, Kaulbachstrasse 45, 80539 Munich, Germany;(3) Faculty of Business and Law, University of Newcastle, Newcastle, Australia;(4) Rotterdam School of Management, Erasmus University, Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlands;(5) Institute for Market-based Management, Ludwig-Maximilians-University Munich, Kaulbachstrasse 45, 80539 Munich, Germany;(6) RSU Rating, Karlstrasse 35, 80333 Munich, Germany |
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Abstract: | Establishing predictive validity of measures is a major concern in marketing research. This paper investigates the conditions
favoring the use of single items versus multi-item scales in terms of predictive validity. A series of complementary studies
reveals that the predictive validity of single items varies considerably across different (concrete) constructs and stimuli
objects. In an attempt to explain the observed instability, a comprehensive simulation study is conducted aimed at identifying
the influence of different factors on the predictive validity of single versus multi-item measures. These include the average
inter-item correlations in the predictor and criterion constructs, the number of items measuring these constructs, as well
as the correlation patterns of multiple and single items between the predictor and criterion constructs. The simulation results
show that, under most conditions typically encountered in practical applications, multi-item scales clearly outperform single
items in terms of predictive validity. Only under very specific conditions do single items perform equally well as multi-item
scales. Therefore, the use of single-item measures in empirical research should be approached with caution, and the use of
such measures should be limited to special circumstances. |
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