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

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Olayan Albalawi , Anu Sirohi , Piyush Kant , Ayed R. A. Alanzi ·

YOU? · · 2022 · Open Access · · DOI: https://doi.org/10.3390/math10132255

This 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.

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Collinearity Statistics Logistic regression Estimator Multicollinearity Parametric statistics Econometrics Mathematics Regression analysis Computer science

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Type: article
Language: en
Landing Page: https://doi.org/10.3390/math10132255
PDF: https://www.mdpi.com/2227-7390/10/13/2255/pdf?version=1656663652
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Cited By: 4
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DOI: https://doi.org/10.3390/math10132255

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

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Language: en

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Publication year: 2022

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Publication date: 2022-06-27

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Authors: Olayan Albalawi, Anu Sirohi, Piyush Kant, Ayed R. A. Alanzi

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Concepts: Collinearity, Statistics, Logistic regression, Estimator, Multicollinearity, Parametric statistics, Econometrics, Mathematics, Regression analysis, Computer science

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Cited by: 4

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