Plotting Results of Sensitivity Analysis for Measurement Error

Source: R/cmsens.R

ggcmsens is used to plot results of cmsens nicely with plotting functions in the ggplot2 package. Additional layers can be added to this plot using other plotting functions in the ggplot2 package.

ggcmsens(
  x,
  errorbar.width = 0.3,
  errorbar.size = 0.3,
  errorbar.position = position_dodge2(width = 0.5),
  point.size = 1,
  point.position = position_dodge2(width = 0.3),
  refline = TRUE,
  refline.colour = "red",
  refline.size = 0.3
)

Arguments

x

an object of class cmsens.me
errorbar.width

width of errorbars for confidence intervals. Default is 0.3.
errorbar.size

size of errorbars for confidence intervals. Default is 0.3.
errorbar.position

position adjustment for confidence intervals, either as a string, or the result of a call to a position adjustment function. Default is position_dodge2(width = 0.5). See geom_errorbar for details.
point.size

size of points for point estimates. Default is 1.
point.position

position adjustment for point estimates, either as a string, or the result of a call to a position adjustment function. Default is position_dodge2(width = 0.3). See geom_errorbar for details.
refline

a logical value. If true, include a reference line at y = 0 when effects are on the difference scale and include a reference line at y = 1 when effects are on the ratio scale. Default is TRUE.
refline.colour

colour of the reference line. Default is red.
refline.size

size of the reference line. Default is 0.3.

See also

cmsens, ggplot2.

Examples


library(CMAverse)
library(ggplot2)

naive <- cmest(data = cma2020, model = "rb", outcome = "contY", 
exposure = "A", mediator = c("M1", "M2"), 
basec = c("C1", "C2"), EMint = TRUE,
mreg = list("logistic", "multinomial"), yreg = "linear",
astar = 0, a = 1, mval = list(0, "M2_0"),
estimation = "imputation", inference = "bootstrap", nboot = 10)

#> 
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x <- cmsens(object = naive, sens = "me", MEmethod = "rc", 
MEvariable = "C1", MEvartype = "con",
MEerror = c(0.1, 0.2))

#> 
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ggcmsens(x) +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 45))


ggcmsens(x) +
ggplot2::coord_flip(xlim = NULL, ylim = NULL, expand = TRUE, clip = "on")