forestplotUV {reportRmd}

Create an univariable forest plot using ggplot2

Description

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

Usage

forestplotUV(
  response,
  covs,
  data,
  id = NULL,
  corstr = NULL,
  model = "glm",
  family = NULL,
  digits = getOption("reportRmd.digits", 2),
  conf.level = 0.95,
  orderByRisk = TRUE,
  colours = "default",
  showEst = TRUE,
  rmRef = FALSE,
  logScale = getOption("reportRmd.logScale", TRUE),
  nxTicks = 5,
  showN = TRUE,
  showEvent = TRUE
)

Arguments

response

character vector with names of columns to use for response

covs

character vector with names of columns to use for covariates

data

dataframe containing your data

id

character vector which identifies clusters. Only used for geeglm

corstr

character string specifying the correlation structure. Only used for geeglm. The following are permitted: '"independence"', '"exchangeable"', '"ar1"', '"unstructured"' and '"userdefined"'

model

fitted model object

family

description of the error distribution and link function to be used in the model. Only used for geeglm

digits

number of digits to round to

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?

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")
forestplotUV(response="orr", covs=c("change_ctdna_group", "sex", "age", "l_size"),
data=pembrolizumab, family='binomial')