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ORIGINAL RESEARCH article

Front. Psychol.
Sec. Quantitative Psychology and Measurement
Volume 14 - 2023 | doi: 10.3389/fpsyg.2023.1245863
This article is part of the Research Topic

New Ideas in Quantitative Psychology and Measurement

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Model-Free Measurement of Case Influence in Structural Equation Modeling

Fathima M. Jaffari1* Jennifer Koran2
  • 1education and training evaluation commission-Qiyas, Saudi Arabia
  • 2Southren illinois university, Quantitative Methodsdepartment, United States

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This study introduces a new model-free case influence measure, the Deleted-One-Covariance-Residual (DOCR), for structural equation modeling and evaluates its performance compared to that of Mahalanobis Distance (MD) and Generalized Cook's Distance (gCD) when the sample size, proportion of target cases to non-target cases, and type of model used to generate the data are manipulated. The findings suggest the DOCR measure generally performed better than MD and gCD in identifying the target cases across all simulated conditions. However, the performance of the DOCR measure under small sample size was not satisfactory, and it raised a red flag about the sensitivity of this measure to small sample size. Therefore, researchers and practitioners should only use the DOCR measure with sufficiently large sample size, but not larger than 600.

Keywords: Influence analysis, Deletion statistics, Mahalanobis distance, generalized Cook's distance, Deleted-One-Covariance-Residual (DOCR)

Received: 23 Jun 2023; Accepted: 12 Dec 2023.

Copyright: © 2023 Jaffari and Koran. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Fathima M. Jaffari, education and training evaluation commission-Qiyas, Riyadh, Saudi Arabia