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Using Attributes of Survey Items to Predict Response Times May Benefit Survey Research
Stefan Schneider1,2,3, Haomiao Jin4, Bart Orriens4
1Center for Self-Report Science & Center for Economic and Social Research, University of Southern California, Los Angeles, CA 90089-3332, USA.
Abstract:
Researchers have become increasingly interested in response times to survey items as a measure of cognitive effort. We used machine learning to develop a prediction model of response times based on 41 attributes of survey items (e.g., question length, response format, linguistic features) collected in a large, general population sample. The developed algorithm can be used to derive reference values for expected response times for most commonly used survey items.
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