Modified outlier diagnostics for the extended exponential regression model with interval and right-censored data

Abstract.: This research will explore the modified outlier diagnostics for the exponentiated exponential regression (EER) model with interval and right-censored data using adjusted residuals and some influence diagnostic measures. The EER model accommodates a monotonically increasing and decreasing...

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Bibliographic Details
Main Authors: Arasan, Jayanthi, Midi, Habshah
Format: Article
Published: Taylor and Francis 2024
Online Access:http://psasir.upm.edu.my/id/eprint/115297/
https://www.tandfonline.com/doi/full/10.1080/03610926.2024.2354814
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Summary:Abstract.: This research will explore the modified outlier diagnostics for the exponentiated exponential regression (EER) model with interval and right-censored data using adjusted residuals and some influence diagnostic measures. The EER model accommodates a monotonically increasing and decreasing hazard rate and reduces to the exponential as a special case. The proposed diagnostics utilize the adjusted residuals based on the bias-corrected bootstrap harmonic mean with random imputation and the measure of curvature. A simulation study is conducted to assess the performances of different methods at various sample sizes, contamination levels, and censoring proportions. The results indicate that the adjusted Cox-Snell residual, martingale residual, and dmax work best to detect outliers in a data set. Finally, the proposed methods are applied to a data set from the Diabetic Retinopathy (DRS) study.