Iterative least squares method for regression analysis with censored data

Abstract

The iterative least squares method (ILSM) is studied for regression analysis with censored data. Simulated data were used to test the performance of this approach, which was compared with the classical least squares (LS) method applied to data in which the censored observations are ignored. A simple algorithm can make the statistical analysis involving censored data more likely to be used by analytical chemists and pharmacists, as is shown by applying the ILSM to real data sets from chromatography and pharmaceutical technology.