Detection of Non-effortful Responses in Personality Surveys

Chen, Yaojia., Rebecca

Permalink

https://hdl.handle.net/2142/117157 Copy

Description

Title

Detection of Non-effortful Responses in Personality Surveys

Author(s)

Chen, Yaojia., Rebecca

Contributor(s)

Zhang, Susu

Issue Date

2021

Keyword(s)

insufficient effort responding, data quality, person-fit statistic, response bias

Abstract

A common data collection strategy used in scientific research is by self-report measures (e.g., surveys). However, such data collected are prone to insufficient effort responding (IER) by the participants. IER affects the validity of the analysis and results in errors that can skew the research outcomes. The purpose of this study is (1) to examine the effectiveness of IER detection utilizing person-fit-based detection method and (2) to compare the IER detection agreement between person-fit-based and instructed-items-based detection methods. We first conducted a simulation study based on the Hungarian version of the Temperament and Character Inventory-Revised questionnaire (TCI-R; Rózsa et al., 2012) to test the detection accuracy of the person-fit-based method. Analysis on the TCI-R dataset was then performed to compare the confirmatory model fit and detection agreement of the two detection methods. The findings suggest the removal of IER helps to increase the data-model fit. In addition, results show a low agreement rate between the person-fit-based detection and the instructed-items-based detection. Potential limitations and suggestions are also offered for further investigation on the topic.

Type of Resource

text

Language

en

Sponsor(s)/Grant Number(s)

llinois Office of Undergraduate Research

Copyright and License Information

Copyright 2021 Rebecca Chen

Owning Collections