View source: R/plot.missingHE.R
plot.missingHE | R Documentation |
missingHE
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
, selection_long
, pattern
or hurdle
.
The graphical layout is obtained from the functions contained in the package ggplot2 and ggthemes.
## S3 method for class 'missingHE'
plot(
x,
prob = c(0.025, 0.975),
class = "scatter",
outcome = "all",
time_plot = NULL,
theme = NULL,
...
)
x |
A |
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, time points (only for longitudinal models) 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'. |
time_plot |
Time point for which plots should be displayed (only for longitudinal models). |
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 |
The function 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
, selection_long
, 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.
A ggplot
object containing the plots specified in the argument class
.
Andrea Gabrio
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.
selection
selection_long
pattern
hurdle
diagnostic
# For examples see the function \code{\link{selection}}, \code{\link{selection_long}},
# \code{\link{pattern}} or \code{\link{hurdle}}
#
#
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