Method of median semi-variance for the analysis of left-censored data: Comparison with other techniques using environmental data

Abstract

In environmental monitoring, variables with analytically non-detected values are commonly encountered. For the statistical evaluation of these data, most of the methods that produce a less biased performance require specific computer programs. In this paper, a statistical method based on the median semi-variance (SemiV) is proposed to estimate the position and spread statistics in a dataset with single left-censoring. The performances of the SemiV method and 12 other statistical methods are evaluated using real and complete datasets. The performances of all the methods are influenced by the percentage of censored data. In general, the simple substitution and deletion methods showed biased performance, with exceptions for L/2, Inter and L/√2 methods that can be used with caution under specific conditions. In general, the SemiV method and other parametric methods showed similar performances and were less biased than other methods. The SemiV method is a simple and accurate procedure that can be used in the analysis of datasets with less than 50% of left-censored data.