plot_expirest_wisle {expirest}

Illustrating the what-if (approach for) shelf life estimate (wisle)

Description

The function plot_expirest_wisle() makes a graphical display of the shelf life estimate done by the expirest_wisle() function.

Usage

plot_expirest_wisle(
  model,
  rl_index = 1,
  show_grouping = "yes",
  response_vbl_unit = NULL,
  x_range = NULL,
  y_range = NULL,
  scenario = "standard",
  mtbs = "verified",
  plot_option = "full",
  ci_app = "line"
)

Arguments

model

An ‘expirest_wisle’ object, i.e. a list returned by the expirest_wisle() function.

rl_index

A positive integer that specifies which of the release limit values that have been handed over to expirest_wisle() should be displayed. The default value is 1.

show_grouping

'r lifecycle::badge("deprecated")' 'show_grouping = \"yes\" or \"no\"' is no longer supported. Use the mtbs parameter instead which allows choosing a specific model, i.e. also the common intercept / common slope case model which was the default model when show_grouping was "no".

response_vbl_unit

A character string that specifies the unit associated with the response variable. The default is NULL.

x_range

A numeric vector of the form c(min, max) that specifies the range of the time variable to be plotted. The default is NULL and the x range is calculated automatically on the basis of the estimated shelf life.

y_range

A numeric vector of the form c(min, max) that specifies the range of the response variable to be plotted. The default is NULL and the y range is calculated automatically on the basis of the time course of the response.

scenario

A character string that specifies if the plot should be extended (with respect to the x axis) up to the “standard scenario” ("standard") or up to the “worst case scenario” ("worst"). The default is "standard".

mtbs

A character string that specifies the “model to be shown”, i.e. either verified, which is the default, or one of cics, dics, dids or dids.pmse. The verified model is the model that was identified through the poolability check. It is thus also one of the possible optional models. The dids model represents the case where a separate model is fitted to the data of each individual batch while the dids.pmse model is the interaction model which includes the batch variable as main effect and in the interaction term with the time variable (batch \times time), i.e. a model where the mean square error is pooled across batches.

plot_option

A character string of either "full", "lean1", "lean2", "basic1" and "basic2" that specifies if additional information should be shown in the plot (option "full") or only basic information (options "lean" and "basic"). Full means the data points, the fitted regression line with the confidence or prediction interval, the specification limit(s) and the estimated shelf life. The default is "full".

ci_app

A character string of either "line" or "ribbon", that specifies the appearance of the confidence interval, i.e. if the limits should be plotted as lines (option "line") or as a shaded ribbon (option "ribbon"). The default is "line".

Details

The function plot_expirest_wisle() uses the data and the information about the linear model that was used for the estimation of the shelf life by aid of the expirest_wisle() function. It plots a graph of the time course of a parameter, a linear regression line fitted to the data and the associated confidence or prediction interval. In addition, it shows features of the worst case scenario shelf life estimation.

For plotting, the ggplot() function from the ‘ggplot2’ package is used. The various arguments can be used to control the appearance of the plot. The ‘ggplot2’ object of the generated plot is contained in the Graph element of the list that is returned by plot_expirest_wisle() and can be used to modify the appearance of the graph.

Value

An object of class ‘plot_expirest_wisle’ is returned invisibly consisting of the following elements:

Model

The ‘expirest_wisle’ object that was passed via the model argument.

Expiery

A data frame of type expiry.

Graph

A ‘ggplot2’ object for the graphical display.

Prediction

A data frame of the predicted values.

text

A data frame of the text elements on the plot.

hlines

A data frame of the horizontal line elements on the plot.

vlines

A data frame of the vertical line elements on the plot.

segments

A data frame of segment line elements on the plot.

arrow

A data frame of arrow elements on the plot.

See Also

expirest_wisle, expirest_osle, plot_expirest_osle.

Examples

# Start by making a "what-if (approach for) shelf life estimation" (wisle)
res1 <-
  expirest_wisle(data = exp1[exp1$Batch %in% c("b2", "b5", "b7"), ],
                 response_vbl = "Potency", time_vbl = "Month",
                 batch_vbl = "Batch", rl = 98, rl_sf = 3, sl = 95,
                 sl_sf = 3, srch_range = c(0, 500), sf_option = "loose")

# Pass the 'expirest_wisle' object on to the plot_expirest_wisle() function.
# This function does not produce any output. It returns a 'plot_expirest_wisle'
# object that is essentially an 'expirest_wisle' object augmented by a 'ggplot'
# object.
gg1 <- plot_expirest_wisle(
  model = res1, rl_index = 1, response_vbl_unit = "%", x_range = NULL,
  y_range = c(93, 105), scenario = "standard", mtbs = "verified",
  plot_option = "full", ci_app = "line")

## Not run: 
  gg1

  # Since the element gg1$Graph is a 'ggplot' object it can be used for further
  # manipulation by aid of 'ggplot2' functions.
  if (requireNamespace("ggplot2")) {
    library(ggplot2)

    gg1$Graph + labs(title = "What-if Shelf Life Estimation (WISLE)",
                     x = "Time [months]", y = "Potency [% LC]") +
      scale_x_continuous(limits = c(-5, 31), breaks = seq(0, 30, 6))
  }

## End(Not run)

# Repeat this for a different intercept / different slope (dids) model.
res2 <-
  expirest_wisle(data = exp1[exp1$Batch %in% c("b4", "b5", "b8"), ],
                 response_vbl = "Potency", time_vbl = "Month",
                 batch_vbl = "Batch", rl = 98, rl_sf = 3, sl = 95,
                 sl_sf = 3, srch_range = c(0, 500), sf_option = "loose")

gg2 <- plot_expirest_wisle(
  model = res2, rl_index = 1, response_vbl_unit = "%", x_range = c(0, 26),
  y_range = c(89, 107),  scenario = "standard",  mtbs = "verified",
  plot_option = "full", ci_app = "ribbon")
## Not run: 
  gg2

## End(Not run)

# In case of different intercept / different slope models, individually fit
# linear models are shown by default, i.e. with the 'mtbs' parameter set
# as "verified". To get the different intercept / different slope model
# displayed where the mean square error is pooled across batches, i.e. the
# dids.pmse model, the 'mtbs' parameter has to be set accordingly.

gg3 <- plot_expirest_wisle(
  model = res2, rl_index = 1, response_vbl_unit = "%", x_range = c(0, 26),
  y_range = c(89, 107),  scenario = "standard",  mtbs = "dids.pmse",
  plot_option = "full", ci_app = "ribbon")
## Not run: 
  gg3

## End(Not run)