Modeling observations with a detection limit using a truncated normal distribution with censoring

@article{Williams2020ModelingOW,
  title={Modeling observations with a detection limit using a truncated normal distribution with censoring},
  author={Justin R. Williams and Hyungwoo Kim and C. Crespi},
  journal={BMC Medical Research Methodology},
  year={2020},
  volume={20}
}
  • Justin R. Williams, Hyungwoo Kim, C. Crespi
  • Published 2020
  • Mathematics, Medicine
  • BMC Medical Research Methodology
  • Background When data are collected subject to a detection limit, observations below the detection limit may be considered censored. In addition, the domain of such observations may be restricted; for example, values may be required to be non-negative. Methods We propose a method for estimating population mean and variance from censored observations that accounts for known domain restriction. The method finds maximum likelihood estimates assuming an underlying truncated normal distribution… CONTINUE READING

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