Survival Analysis with Multivariate Adaptive Regression Splines using Cox-Snell Residual
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Date
2015
Authors
Dauda, K. A.
Yahya, W. B.
Banjoko, A. W.
Journal Title
Journal ISSN
Volume Title
Publisher
Faculty of Computer and Applied Computer Science, Tibiscus University of Timisoara, Romania
Abstract
Multivariate Adaptive Regression Splines
(MARS) are a generalization of stepwise linear regression
method that is often employed to improve the efficiency
of regression models. It is a useful tool to identify
linear/nonlinear and interactions effects between a set of
metrical and categorical covariates in regression models.
In this study, the use of a modified Cox-Snell Residuals to
Survival Analysis with MARS was proposed. The
proposed method was compared with Martingale Residual
in the Survival MARS setting. These two residual types
were used as responses in the Cox proportional hazard
modeling in the MARS implementations. Results from
simulation studies revealed that the proposed method
fitted the data better than the Martingale residual
However, further results from Monte-Carlo experiment
showed that the two residual types performed better than the
classical Cox Proportional Hazard (CPH) method. These
methods were applied on real life dataset on Pneumocystis
Carinii Pneumonia and all the results obtained actually
validated those got from the simulation studies
Description
Keywords
MARS, Martingale Residual, Modified Cox-Snell Residual, PCP, CART