A Comparative Study of the Bias Correction Methods for Differential Item Functioning Analysis in Logistic Regression with Rare Events Data
Joint Authors
Jafari, Peyman
Bagheri, Zahra
Faghih, Marjan
Stevanovic, Dejan
Ayatollahi, Seyyed Mohhamad Taghi
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-25
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The logistic regression (LR) model for assessing differential item functioning (DIF) is highly dependent on the asymptotic sampling distributions.
However, for rare events data, the maximum likelihood estimation method may be biased and the asymptotic distributions may not be reliable.
In this study, the performance of the regular maximum likelihood (ML) estimation is compared with two bias correction methods including weighted logistic regression (WLR) and Firth's penalized maximum likelihood (PML) to assess DIF for imbalanced or rare events data.
The power and type I error rate of the LR model for detecting DIF were investigated under different combinations of sample size, moderate and severe magnitudes of uniform DIF (DIF = 0.4 and 0.8), sample size ratio, number of items, and the imbalanced degree (τ).
Indeed, as compared with WLR and for severe imbalanced degree (τ = 0.069), there were reductions of approximately 30% and 24% under DIF = 0.4 and 27% and 23% under DIF = 0.8 in the power of the PML and ML, respectively.
The present study revealed that the WLR outperforms both the ML and PML estimation methods when logistic regression is used to evaluate DIF for imbalanced or rare events data.
American Psychological Association (APA)
Faghih, Marjan& Bagheri, Zahra& Stevanovic, Dejan& Ayatollahi, Seyyed Mohhamad Taghi& Jafari, Peyman. 2020. A Comparative Study of the Bias Correction Methods for Differential Item Functioning Analysis in Logistic Regression with Rare Events Data. BioMed Research International،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1131784
Modern Language Association (MLA)
Faghih, Marjan…[et al.]. A Comparative Study of the Bias Correction Methods for Differential Item Functioning Analysis in Logistic Regression with Rare Events Data. BioMed Research International No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1131784
American Medical Association (AMA)
Faghih, Marjan& Bagheri, Zahra& Stevanovic, Dejan& Ayatollahi, Seyyed Mohhamad Taghi& Jafari, Peyman. A Comparative Study of the Bias Correction Methods for Differential Item Functioning Analysis in Logistic Regression with Rare Events Data. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1131784
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1131784