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-...
In many situations information from a sample of individuals can be supplemented by population level ...
Economists and other social scientists often face situations where they have access to two datasets ...
We discuss Bayesian log-linear models for incomplete contingency tables with both missing and interv...
Abstract. Observed data sets containing values above or below the analytical threshold of measuring ...
Environmental data sets of pollutant concentrations in air, water, and soil frequently include unqua...
In this chapter we deal with population size estimation in a particularly interesting case. We assum...
A new model to make inferences about population characteristics from experimental datasets is presen...
Abstract. We consider random variables which can be subject to both censoring and measurement errors...
In order to make statistical inference, that is drawing conclusions from a sample to describe a popu...
The main classes of statistical treatments that have been used to determine if two groups of censore...
Approaches based on the maximum likelihood (ML) method and on the order statistics are described and...
In many situations information from a sample of individuals can be supplemented by population level ...
We detail the basic theory for regression models in which dependent variables are censored or underl...
A frequent problem that appears in practical survival data analysis is censoring. A censored observa...
Estimating population size is an important task for epidemiologists and ecologists alike, for purpos...
In many situations information from a sample of individuals can be supplemented by population level ...
Economists and other social scientists often face situations where they have access to two datasets ...
We discuss Bayesian log-linear models for incomplete contingency tables with both missing and interv...
Abstract. Observed data sets containing values above or below the analytical threshold of measuring ...
Environmental data sets of pollutant concentrations in air, water, and soil frequently include unqua...
In this chapter we deal with population size estimation in a particularly interesting case. We assum...
A new model to make inferences about population characteristics from experimental datasets is presen...
Abstract. We consider random variables which can be subject to both censoring and measurement errors...
In order to make statistical inference, that is drawing conclusions from a sample to describe a popu...
The main classes of statistical treatments that have been used to determine if two groups of censore...
Approaches based on the maximum likelihood (ML) method and on the order statistics are described and...
In many situations information from a sample of individuals can be supplemented by population level ...
We detail the basic theory for regression models in which dependent variables are censored or underl...
A frequent problem that appears in practical survival data analysis is censoring. A censored observa...
Estimating population size is an important task for epidemiologists and ecologists alike, for purpos...
In many situations information from a sample of individuals can be supplemented by population level ...
Economists and other social scientists often face situations where they have access to two datasets ...
We discuss Bayesian log-linear models for incomplete contingency tables with both missing and interv...