Using Partial Least Squares Regression in Lifetime Analysis

The problem of collinearity among right-censored data is considered in multivariate linear regression by combining mean imputation and the Partial Least Squares (PLS) methods. The purpose of this paper is to investigate the performance of PLS regression when explanatory variables are strongly correlated financial ratios. It is shown that ignoring the presence of censoring in the data can cause a bias. The proposed methodology is applied to a data set describing the financial status of some small and medium-sized Tunisian firms. The derived model is interesting to be able to predict the lifetime of a firm until the occurrence of the failure event.