Skewed Slash Censored Quantile Regression

Maryam Tatari (), Hojjat Zeraati (), Mehdi Yaseri (), Amir Kasaeian (), Akram Yazdani (), Seyed Asadollah Mousavi () and Christian E. Galarza ()
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Maryam Tatari: Tehran University of Medical Sciences
Hojjat Zeraati: Tehran University of Medical Sciences
Mehdi Yaseri: Tehran University of Medical Sciences
Amir Kasaeian: Tehran University of Medical Sciences
Akram Yazdani: Kashan University of Medical Sciences
Seyed Asadollah Mousavi: Tehran University of Medical Sciences
Christian E. Galarza: Escuela Superior Politécnica del Litoral

Sankhya B: The Indian Journal of Statistics, 2025, vol. 87, issue 1, No 11, 292-318

Abstract: Abstract In survival studies, the response variable is the time to desired event, which usually has skewness and censoring. For this reason, its mean modeling does not provide a complete picture of the density function. The quantile regression model investigates the effect of covariates in different percentiles by modeling duration time. The skewed slash distribution, having an addition parameter ( $$\upsilon $$ υ ), can change the tail width of the density function by changing its value, and is a more flexible distribution than other asymmetric distributions. We considered the skewed slash quantile regression model for survival data that interpret the effect of covariates on time-to-event. Likelihood-based approach and Nelder-Mead algorithm were used to fit the model. An application to data from AML patients receiving allo-HCT was presented to illustrate the theory and method developed in this paper. The Skewed slash distribution, by matching skewed data sets with heavy tails (Setting with the $$\varvec{\nu }$$ ν parameter), is useful for analyzing skewed and heavy tail data sets.

Keywords: Quantile regression; Skewed slash distribution; survival data; Numerical solution approach; Primary 62N02; Secondary 62G08; 62P10 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13571-025-00355-1

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