plot.hce {maraca}

Generic function to plot the hce object using plot().

Description

Generic function to plot the hce object using plot().

Usage

## S3 method for class 'hce'
plot(
  x,
  step_outcomes = NULL,
  last_outcome = "C",
  arm_levels = c(active = "A", control = "P"),
  continuous_grid_spacing_x = 10,
  trans = c("identity", "log", "log10", "sqrt", "reverse")[1],
  density_plot_type = c("default", "violin", "box", "scatter")[1],
  vline_type = NULL,
  fixed_followup_days = NULL,
  compute_win_odds = FALSE,
  step_types = "tte",
  last_type = "continuous",
  theme = "maraca",
  lowerBetter = FALSE,
  tte_outcomes = lifecycle::deprecated(),
  continuous_outcome = lifecycle::deprecated(),
  ...
)

Arguments

x

an object of S3 class 'hce'.

step_outcomes

A vector of strings containing the outcome labels for all outcomes displayed as part of the step function on the left side of the plot. The order is kept for the plot. By default (when set to NULL) this is automatically updated by taking the non-continuous outcomes from the GROUP variable in alphabetical order.

last_outcome

A single string containing the last outcome label displayed on the right side of the plot. Default value "C".

arm_levels

A named vector of exactly two strings, mapping the values used for the active and control arms to the values used in the data. The names must be "active" and "control" in this order. Note that this parameter only need to be specified if you have labels different from "active" and "control".

continuous_grid_spacing_x

The spacing of the x grid to use for the continuous section of the plot.

trans

the transformation to apply to the x-axis scale for the last outcome. Possible values are "identity", "log" (only for continuous endpoint), "log10" (only for continuous endpoint), "sqrt" (only for continuous endpoint) and "reverse". The default value is "identity".

density_plot_type

The type of plot to use to represent the density. Accepts "default", "violin", "box" and "scatter".

vline_type

what the vertical dashed line should represent. Accepts "median" (only for continuous last endpoint), "mean", "none" and NULL (default). By default (vline_type = NULL), vline_type will be set to "median" for a continuous last endpoint and to "mean" for a binary last endpoint.

fixed_followup_days

Not needed if HCE object contains information on fixed follow-up days in the study (column PADY or TTEfixed, depending on hce version). Otherwise, this argument must be specified to give the fixed follow-up days in the study. Can be a single integer value for all tte-outcomes or a vector with one integer value per tte-outcome. Note: If argument is specified and HCE object also contains PADY or TTEfixed column, then fixed_followup_days argument is used.

compute_win_odds

If TRUE compute the win odds, otherwise (default) don't compute them.

step_types

The type of each outcome in the step_outcomes vector. Can be a single string (if all outcomes of same type) or a vector of same length as step_outcomes. Possible values in the vector are "tte" (default) or "binary".

last_type

A single string giving the type of the last outcome. Possible values are "continuous" (default), "binary" or "multinomial".

theme

Choose theme to style the plot. The default theme is "maraca". Options are "maraca", "maraca_old", "color1", "color2" and none". For more details, check the vignette called "Maraca Plots - Themes and Styling". [companion vignette for package users](themes.html)

lowerBetter

Flag for the final outcome variable, indicating if lower values are considered better/advantageous. This flag is need to make sure the win odds are calculated correctly. Default value is FALSE, meaning higher values are considered advantageous.

tte_outcomes

Deprecated and substituted by the more general 'step_outcomes'. A vector of strings containing the time-to-event outcome labels. The order is kept for the plot.

continuous_outcome

Deprecated and substituted by the more general 'last_outcome'. A single string containing the continuous outcome label.

...

not used

Value

Returns ggplot2 plot of the hce object.

Examples

Rates_A <- c(1.72, 1.74, 0.58, 1.5, 1)
Rates_P <- c(2.47, 2.24, 2.9, 4, 6)
hce_dat <- hce::simHCE(n = 2500, TTE_A = Rates_A, TTE_P = Rates_P,
             CM_A = -3, CM_P = -6, CSD_A = 16, CSD_P = 15, fixedfy = 3,
             seed = 31337)
plot(hce_dat)
plot(hce_dat, fixed_followup_days = 3 * 365)