Title:
Parametric Frailty Analysis in Presence of Collinearity: An Application to Assessment of Infant Mortality

dc.contributor.authorOlayan Albalawi
dc.contributor.authorAnu Sirohi
dc.contributor.authorPiyush Kant Rai
dc.contributor.authorAyed R. A. Alanzi
dc.date.accessioned2026-02-07T11:00:08Z
dc.date.issued2022
dc.description.abstractThis paper analyzes the time to event data in the presence of collinearity. To address collinearity, the ridge regression estimator was applied in multiple and logistic regression as an alternative to the maximum likelihood estimator (MLE), among others. It has a smaller mean square error (MSE) and is therefore more precise. This paper generalizes the approach to address collinearity in the frailty model, which is a random effect model for the time variable. A simulation study is conducted to evaluate its performance. Furthermore, the proposed method is applied on real life data taken from the largest sample survey of India, i.e., national family health survey (2005–2006) data to evaluate the association of different determinants on infant mortality in India. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
dc.identifier.doi10.3390/math10132255
dc.identifier.issn22277390
dc.identifier.urihttps://doi.org/10.3390/math10132255
dc.identifier.urihttps://dl.bhu.ac.in/bhuir/handle/123456789/41040
dc.publisherMDPI
dc.subjectcollinearity
dc.subjectfrailty model
dc.subjectinfant mortality
dc.subjectmaximum likelihood estimation
dc.subjectridge regression
dc.titleParametric Frailty Analysis in Presence of Collinearity: An Application to Assessment of Infant Mortality
dc.typePublication
dspace.entity.typeArticle

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