npde.cens.method: Method used to handle censored data

In npde: Normalised prediction distribution errors for nonlinear mixed-effect models

Description

Specifies the method used to handle censored data (data below the limit of quantification LOQ)

Details

More details can be found in the PDF documentation.

Value

The following methods are available in the npde library:

omit

pd and npde for censored data will be set to NA

cdf

for an observation ycens_ij under the LOQ, a pd_ij will be imputed in the uniform distribution [0-pLOQ_ij] where pLOQ_ij is the probability that y_ij is below LOQ, according to the model; the predictive distribution will then be used to obtain a corresponding y*_ij. This is also performed for all simulated data, and the npde are then computed on the completed dataset containing the observed y_ij for the uncensored data and the y*_ij imputed for the censored data. This method is the default.

ipred

an observation ycens_ij is replaced by the individual prediction according to the model (ipred, which must be present in the dataset). Simulated data are left untouched.

ypred

an observation ycens_ij is replaced by the population prediction according to the model (ypred). Simulated data are left untouched.

loq

an observation ycens_ij is replaced by the value of the LOQ. Simulated data are left untouched.

References

K. Brendel, E. Comets, C. Laffont, C. Laveille, and F. Mentre. Metrics for external model evaluation with an application to the population pharmacokinetics of gliclazide. Pharmaceutical Research, 23:2036–49, 2006.

npde documentation built on May 2, 2019, 5:23 p.m.