For partykit or rpart based tree models, visualize tree structure and subgroup (node) specific treatment estimates. Plots (ggparty) can include other node-specific information, see below for details.
plot_tree(
object,
prob.thres = ">0",
plots = "outcome",
nudge_out = 0.1,
width_out = 0.5,
nudge_dens = ifelse(plots == "both", 0.3, 0.1),
width_dens = 0.5,
...
)PRISM or submod_train object
Probability threshold, ex: P(Mean(A=1 vs A=0)>c. Default=NULL, which defaults to using ">0", unless param="cox", which "P(HR(A=1 vs A=0))<1". If a density plot is included, setting prob.thres=">c" will use green colors for values above c, and red colors for values below c. If tree.thres="<c", the reverse color scheme is used.
Type of plots to include in each node of the "tree" plot. Default="outcome". For non-survival data, if the fitted PRISM object (x) does not include patient-level estimates (ple="None"), or if param="lm", this will plot the observed outcomes (Y) by the treatment assignment (A). If the fitted PRISM object includes patient-level estimates (ex: ple="ranger"), this includes box-plots of the model-based (if param="ple") or double-robust based (if param="dr") counter-factual estimates of E(Y|X,A=a) for continuous outcomes or Prob(Y=1|X,A=a) for binary outcomes (truncated to 0,1). For survival data, Kaplan-Meier based survival estimates are plotted by treatment group. For "density", the estimated probability density of the treatment effects is shown (normal approximation, unless resampling is used). "both" include the "outcome" and "density" plots. If tree.plots = "none", then only the tree structure is shown.
Nudge tree outcome plot (see ggparty for details)
Width of tree outcome plot (see ggparty for details)
Nudge tree density plot
Width of density tree outcome plot
Additional arguments (currently ignored).
Plot (ggplot2) object