npde.plot.covariate: Covariate diagnostic plots

In npde: Normalised Prediction Distribution Errors for Nonlinear Mixed-Effect Models

Covariate diagnostic plots

Description

Boxplot of the selected variable versus categories of covariates

Usage

npde.plot.covariate(npdeObject, which.y="npd", ...)

Arguments

npdeObject	an object returned by a call to npde or autonpde
which.y	a string specifying the variable on the Y-axis (one of "yobs", "npde", "pd", "npd")
...	additional arguments to be passed on to the function, to control which metric (npde, pd, npd) is used or to override graphical parameters (see the PDF document for details, as well as set.plotoptions and npdeControl)

Details

For a categorical covariate, boxplots are produced for each category. Continous covariates are split into quantile (by default, first quartile (<Q1), interquartile range (Q1-Q3) and upper quartile (>Q3), but the number of categories can be set by using the ncat argument).

For each category, the median according to simulations under the model is shown (it can be suppressed by using the argument bands=FALSE)..

Value

a ggplot object or a list of ggplot objects (grobs)

Author(s)

Emmanuelle Comets <[e-mail]>

References

K. Brendel, E. Comets, C. Laffont, F. Mentre F. Evaluation of different tests based on observations for external model evaluation of population analyses. Journal of Pharmacokinetics and Pharmacodynamics, 37:49-65, 2010.

See Also

npde, autonpde, set.plotoptions, npdeControl

npde documentation built on July 9, 2023, 5:20 p.m.