The objective of this work was to develop a methodology for statistical analysis of monitoring data of chemical compounds in drinking water supply systems in Brazil, using data from Sisagua (Drinking Water Quality Surveillance Information System). Initially, the inconsistencies in the database were identified and adjusted. Then, the descriptive statistics were estimated using the Kaplan-Meier (KM) method, evaluating its applicability in different censored data sets. The descriptive parameters were compared with the substitution method. The substitution method showed susceptibility to biased estimates, especially for groups of compounds containing high percentage of censored data and with high limits of quantification and detection, leading to higher descriptive parameters compared to KM method. This work reinforces the need to use appropriate methods for analyzing environmental data and evidences that the analysis of this type of data may be complex. The methods proposed here can help environmental scientists to deal with this issue, providing a systematic procedure to check and solve consistency problems, as well as presenting a nonparametric approach for computing descriptive statistics for environmental monitoring data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.