PlotModelingResults: Plot factor trajectories

In rchendrickson/pmsimstats: Personalized medicine simulated statistics

Plot factor trajectories

Description

PlotModelingResults plots basic output relating to the peformance of each trial design across a parameter space

Usage

PlotModelingResults(
  data,
  param2plot,
  param2vary,
  param2hold,
  param2nothold,
  labelcode
)

Arguments

data	the $results component of the output of generateSimulatedResults
param2plot	What value to plot as the heatmap out put. Can be power, mean_frac_NA, mean_beta, mean_betaSE, sd_beta
param2vary	4 params to vary and plot across the created space
param2hold	Params to keep constant
param2nothold	Things to let vary freely (if e.g. they are linked to another intentionally varied parameter)
labelcode	A mapping between interal variable names and figure labels

Value

a ggplot object containing the plot

Examples

data(results_core)
  param2vary<-c("trialdesign","N","c.bm","censorparamset")
  param2hold<-data.table(blparamset=1,respparamset=1,carryover_t1half=0)
  param2nothold<-c("c.cfct","modelparamset")
  param2plot<-"power" # Options: power, mean_frac_NA, mean_beta, mean_betaSE, sd_beta...
  p1<-PlotModelingResults(simresults,param2plot,param2vary,param2hold,param2nothold)
 # See vignettes for additional details

rchendrickson/pmsimstats documentation built on Nov. 28, 2024, 11:05 a.m.