plot.missingHE: Plot method for the imputed data contained in the objects of class `missingHE`

Description

Produces a plot of the observed and imputed values (with credible intervals) for the effect and cost outcomes from a Bayesian cost-effectiveness analysis model with two treatment arms, implemented using the function selection, pattern or hurdle. The graphical layout is obtained from the functions contained in the package ggplot2 and ggthemes.

Usage

# S3 method for missingHE
plot(
  x,
  prob = c(0.025, 0.975),
  class = "scatter",
  outcome = "all",
  theme = NULL,
  ...
)

Value

A ggplot object containing the plots specified in the argument class.

Arguments

x: A missingHE object containing the results of the Bayesian model for cost-effectiveness analysis.
prob: A numeric vector of probabilities representing the upper and lower CI sample quantiles to be calculated and returned for the imputed values.
class: Type of the plot comparing the observed and imputed outcome data. Available choices are 'histogram' and 'scatter' for a histogram or a scatter plot of the observed and imputed outcome data, respectively.
outcome: The outcome variables that should be displayed. Options are: 'all' (default) which shows the plots for both treatment arms and types of outcome variables; 'effects' and 'costs' which show the plots for the corresponding outcome variables in both arms; 'arm1' and 'arm2' which show the plots by the selected treatment arm. To select the plots for a specific outcome in a specific treatment arm the options that can be used are 'effects_arm1', 'effects_arm2', 'costs_arm1' or 'costs_arm2'.
theme: Type of ggplot theme among some pre-defined themes, mostly taken from the package ggthemes. For a full list of available themes see details.
...: Additional parameters that can be provided to manage the output of plot.missingHE.

Author

Andrea Gabrio

Details

The funciton produces a plot of the observed and imputed effect and cost data in a two-arm based cost-effectiveness model implemented using the function selection, pattern or hurdle. The purpose of this graph is to visually compare the outcome values for the fully-observed individuals with those imputed by the model for the missing individuals. For the scatter plot, imputed values are also associated with the credible intervals specified in the argument prob. The argument theme allows to customise the graphical aspect of the plots generated by plot.missingHE and allows to choose among a set of possible pre-defined themes taken form the package ggtheme. For a complete list of the available character names for each theme and scheme set, see ggthemes and bayesplot.

References

Daniels, MJ. Hogan, JW. (2008) Missing Data in Longitudinal Studies: strategies for Bayesian modelling and sensitivity analysis, CRC/Chapman Hall.

Molenberghs, G. Fitzmaurice, G. Kenward, MG. Tsiatis, A. Verbeke, G. (2015) Handbook of Missing Data Methodology, CRC/Chapman Hall.

Examples

Run this code

#For examples see the function selection, pattern or hurdle
#
#

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