forestplotMV {reportRmd}

Create a multivariable forest plot using ggplot2

Description

This function will send and take log or logistic regression fit from glm or geeglm from mvsum function, and display the OR or RR for each variable on the appropriate log scale.

Usage

forestplotMV(
  model,
  data,
  conf.level = 0.95,
  orderByRisk = TRUE,
  colours = "default",
  showEst = TRUE,
  rmRef = FALSE,
  digits = getOption("reportRmd.digits", 2),
  logScale = getOption("reportRmd.logScale", TRUE),
  nxTicks = 5,
  showN = TRUE,
  showEvent = TRUE
)

Arguments

model

an object output from the glm or geeglm function, must be from a logistic regression

data

dataframe containing your data

conf.level

controls the width of the confidence interval

orderByRisk

logical, should the plot be ordered by risk

colours

can specify colours for risks less than, 1 and greater than 1.0. Default is red, black, green

showEst

logical, should the risks be displayed on the plot in text

rmRef

logical, should the reference levels be removed for the plot?

digits

number of digits to use displaying estimates

logScale

logical, should OR/RR be shown on log scale, defaults to TRUE, or reportRmd.logScale if set. See https://doi.org/10.1093/aje/kwr156 for why you may prefer a linear scale.

nxTicks

Number of tick marks supplied to the log_breaks function to produce

showN

Show number of observations per variable and category

showEvent

Show number of events per variable and category

Value

a plot object

Examples

data("pembrolizumab")
glm_fit = glm(orr~change_ctdna_group+sex+age+l_size,
data=pembrolizumab,family = 'binomial')
forestplotMV(glm_fit)