statforbiology (version 0.9.9)

getPlotData: Get the data for plotting with ggplot()

Description

This method works on a model object and retrieves the data for plotting the observed values (average or all data) and predictions from model fit. It is mainly meant to be used with ggplot()

Usage

getPlotData(obj, ...)
# S3 method for drc
getPlotData(obj, xlim = NULL, gridsize = 100, type = c("average", "all"), ...)
# S3 method for nls
getPlotData(obj, xlim = NULL, gridsize = 100, type = c("average", "all"), ...)
# S3 method for drcte
getPlotData(
  obj,
  xlim = NULL,
  gridsize = 100,
  npmle.type = c("interpolation", "midpoint", "right", "left", "none"),
  ...
)

Value

This function returns a list of two elements: 'plotPoints' is a dataframe containing the observed data, 'plotFits' is a dataframe containing model predictions

Arguments

obj

A fitted model object. Methods are provided for drc, drcte and nls objects

...

Other additional arguments.

xlim

a vector. The interval for the predictor in which predictions are to be obtained

gridsize

numeric. Number of points in the grid (within xlim) used for predictions.

type

a character string specifying whether all the observed points should be plotted (type = "all") or whether the response should be averaged over the levels of the predictor (type = "all"). It is disregarded for drcte objects

npmle.type

a character string. For drcte objects, the NPMLE of the cumulative density function is only specified at the end of each inspection interval, while it is not unique within each interval. This argument specifies how the CDF increases within each interval: possible values are "interpolation" (it is assumed that the CDF increases progressively), "left" (the CDF increases at the beginning of each interval), "right" (the CDF increases at the end of each interval; it is very common in survival analysis) and "midpoint" (the CDF increases in the middle of each interval; it is very common in survival analysis). This argument is neglected with nls and drc objects.

Author

Andrea Onofri

Examples

fileName <- "https://www.casaonofri.it/_datasets/metamitron.csv"
metamitron <- read.csv(fileName)
mod <- drm(Conc ~ Time, fct = EXD.2(),
           data = metamitron, curveid = Herbicide)
retVal <- getPlotData(mod)
library(ggplot2)
ggplot() +
  geom_point(data = retVal$plotPoints, mapping = aes(x = Time, y = Conc)) +
  geom_line(data = retVal$plotFits, mapping = aes(x = Time, y = Conc)) +
  facet_wrap(~ Herbicide)