Literature DB >> 32158024

Methods of Detecting Insufficient Effort Responding: Comparisons and Practical Recommendations.

Maxwell Hong1, Jeffrey T Steedle2, Ying Cheng1.   

Abstract

Insufficient effort responding (IER) affects many forms of assessment in both educational and psychological contexts. Much research has examined different types of IER, IER's impact on the psychometric properties of test scores, and preprocessing procedures used to detect IER. However, there is a gap in the literature in terms of practical advice for applied researchers and psychometricians when evaluating multiple sources of IER evidence, including the best strategy or combination of strategies when preprocessing data. In this study, we demonstrate how the use of different IER detection methods may affect psychometric properties such as predictive validity and reliability. Moreover, we evaluate how different data cleansing procedures can detect different types of IER. We provide evidence via simulation studies and applied analysis using the ACT's Engage assessment as a motivating example. Based on the findings of the study, we provide recommendations and future research directions for those who suspect their data may contain responses reflecting careless, random, or biased responding.
© The Author(s) 2019.

Keywords:  data quality; insufficient effort responding; outlier detection; validity evidence

Year:  2019        PMID: 32158024      PMCID: PMC7047258          DOI: 10.1177/0013164419865316

Source DB:  PubMed          Journal:  Educ Psychol Meas        ISSN: 0013-1644            Impact factor:   2.821


  18 in total

1.  Detection of back random responding: effectiveness of MMPI-2 and Personality Assessment Inventory validity indices.

Authors:  Michael E Clark; Ronald J Gironda; Robert W Young
Journal:  Psychol Assess       Date:  2003-06

2.  Is psychology suffering from a replication crisis? What does "failure to replicate" really mean?

Authors:  Scott E Maxwell; Michael Y Lau; George S Howard
Journal:  Am Psychol       Date:  2015-09

3.  A flexible full-information approach to the modeling of response styles.

Authors:  Carl F Falk; Li Cai
Journal:  Psychol Methods       Date:  2015-12-07

4.  The lz(p)* Person-Fit Statistic in an Unfolding Model Context.

Authors:  Jorge N Tendeiro
Journal:  Appl Psychol Meas       Date:  2016-09-29

5.  Insufficient effort responding: examining an insidious confound in survey data.

Authors:  Jason L Huang; Mengqiao Liu; Nathan A Bowling
Journal:  J Appl Psychol       Date:  2014-12-15

6.  Measurement error and the replication crisis.

Authors:  Eric Loken; Andrew Gelman
Journal:  Science       Date:  2017-02-10       Impact factor: 47.728

7.  When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions.

Authors:  Mijke Rhemtulla; Patricia É Brosseau-Liard; Victoria Savalei
Journal:  Psychol Methods       Date:  2012-07-16

8.  Reversed item bias: an integrative model.

Authors:  Bert Weijters; Hans Baumgartner; Niels Schillewaert
Journal:  Psychol Methods       Date:  2013-05-06

9.  The prediction of semantic consistency in self-descriptions: characteristics of persons and of terms that affect the consistency of responses to synonym and antonym pairs.

Authors:  L R Goldberg; J M Kilkowski
Journal:  J Pers Soc Psychol       Date:  1985-01

10.  Clarifying the Effect of Test Speededness.

Authors:  Maxwell R Hong; Ying Cheng
Journal:  Appl Psychol Meas       Date:  2018-12-19
View more
  3 in total

1.  Asymptotically Corrected Person Fit Statistics for Multidimensional Constructs with Simple Structure and Mixed Item Types.

Authors:  Maxwell Hong; Lizhen Lin; Ying Cheng
Journal:  Psychometrika       Date:  2021-04-01       Impact factor: 2.500

2.  Parameter Estimation Accuracy of the Effort-Moderated Item Response Theory Model Under Multiple Assumption Violations.

Authors:  Joseph A Rios; James Soland
Journal:  Educ Psychol Meas       Date:  2020-09-02       Impact factor: 3.088

3.  Detecting Careless Responding in Survey Data Using Stochastic Gradient Boosting.

Authors:  Ulrich Schroeders; Christoph Schmidt; Timo Gnambs
Journal:  Educ Psychol Meas       Date:  2021-04-19       Impact factor: 2.821

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.