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DRJP/cutoff

R package: determining cutoff values from bimodal data

cutoff

This is an R package that implements the method used in Trang et al. (2015). It fits a finite mixture model (Schlattman 2009)
to a bimodal distribution using the Expectation-Maximization algorithm (Do and Batzoglou 2008). Confidence interval of the
mixture parameter is found using the method of Oakes (1999). The fitted finite mixture model is then used to calculate a cutoff
value that separates the data in two groups, given a type-1 error to belong to one of the two modes.

References

  • Do, C. B., and S. Batzoglou. 2008. What is the expectation maximization algorithm? Nat Biotechnol 26:897–899.
  • Oakes, D. 1999. Direct calculation of the information matrix via the EM algorithm. J R Statist Soc B 61:479–482.
  • Schlattmann, P. 2009. Medical Applications of Finite Mixture Models. Springer Verlag.
  • Trang, N. V., M. Choisy, N. T. Nakagomi, N. T. U. Chinh, Y. H. Doan, T. Yamashiro, J. E. Bryant, et al. 2015. Determination of
    cut-off cycle threshold values in routine RT–PCR assays to assist differential diagnosis of norovirus in children hospitalized
    for acute gastroenteritis. Epidemiol Infect. In press.

Contributors

Created March 14, 2024
Updated March 14, 2024