plot-ihwResult-method: Plot functions for IHW

In nignatiadis/IHW: Independent Hypothesis Weighting

Plot functions for IHW

Description

See the vignette for usage examples.

Usage

## S4 method for signature 'ihwResult'
plot(
  x,
  x_axis = c(weights = "group", decisionboundary = "covariate")[what],
  what = "weights",
  scale = covariate_type(x)
)

Arguments

x	Object of class ihwResult
x_axis	Character: "group" or "covariate". Default is "group" if "what" is "weights", and "covariate" if "what" is "decisionboundary".
what	Character: "weights" or "decisionboundary"
scale	Character: "ordinal" or "nominal"

Value

A ggplot2 object.

Examples

   save.seed <- .Random.seed; set.seed(1)
   X   <- runif(20000, min = 0.5, max = 4.5) # covariate
   H   <- rbinom(20000, 1, 0.1)              # hypothesis true or false
   Z   <- rnorm(20000, H*X)                  # z-score
   .Random.seed <- save.seed
   pvalue <- 1-pnorm(Z)                      #pvalue
   ihw_res <- ihw(pvalue, X, .1)
   plot(ihw_res)

nignatiadis/IHW documentation built on Aug. 22, 2023, 2:11 p.m.