Using Rasch-Based Indices to Detect Careless Responses in Surveys With Missing Data

• In Event: AERA Roundtable Session Saturday 1:30 pm Four Seasons Ballroom 2-3
  In Roundtable Session: Multidisciplinary Measurement Using Rasch Modeling (Table 4)

Abstract

Careless or insufficient effort responses compromise the accuracy of assessment tools or survey instruments. Previous research has explored the detection and classification of careless responses without specifically addressing the issue of missing data. Missing responses are prevalent in survey research and can obstruct the identification of careless responses. This research aims to use Rasch-based indices and timing data to detect careless responses in surveys with missing data. Integrating response time as a variable enhances detection accuracy. Specifically, we will explore the use of person-fit statistics as additional Careless Responding (CR) indices to complement and increase the accuracy of data preparation and analysis.

Authors

• Yuan Ge, The College Board

• Stefanie A. Wind, University of Alabama

• Eli Andrew Jones, University of Memphis

• Chia-Lin Tsai, University of Northern Colorado