Mathematics (Jun 2022)

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

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

DOI
https://doi.org/10.3390/math10132255
Journal volume & issue
Vol. 10, no. 13
p. 2255

Abstract

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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.

Keywords