A new model for the inference of population characteristics from experimental data using uncertainties

This paper extends a recent report on a model to establish population characteristics to include censored data. The theoretical background is given. The application given in this paper is limited to left-censored data, i.e. less than values, but the principles can also be adopted for other types of censored data. The model gives robust estimates of population characteristics for datasets with complicated underlying distributions including less than values of different magnitude and less than values exceeding the values of numerical data. The extended model is illustrated with simulated datasets, data from interlaboratory studies and temporal trend data on dissolved cadmium in the Rhine river. The calculations confirm that inclusion of left-censored values in the computation of population characteristics improves assessment procedures.