Create a multivariable forest plot using ggplot2

This function creates forest plots from fitted regression models, with optional inclusion of unadjusted estimates. It uses m_summary for robust data extraction and properly handles factor level ordering and reference levels.

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

Arguments

model

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

data

dataframe containing your data (required if include_unadjusted = TRUE)

include_unadjusted

logical, should unadjusted estimates be included? Default is FALSE

conf.level

controls the width of the confidence interval (default 0.95)

colours

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

showEst

logical, should the risks be displayed on the plot in text? Default is TRUE

showRef

logical, should reference levels be shown? Default is TRUE

digits

number of digits to use displaying estimates (default 2)

logScale

logical, should OR/RR be shown on log scale? Defaults to TRUE. See https://doi.org/10.1093/aje/kwr156 for why you may prefer a linear scale

nxTicks

Number of tick marks for x-axis (default 5)

showN

Show number of observations per variable and category (default TRUE)

showEvent

Show number of events per variable and category (default TRUE)

xlim

Numeric vector of length 2 specifying x-axis limits (ex c(0.2, 5))

Value

a ggplot object

Examples

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

# Adjusted only
forestplotMV(glm_fit, data = pembrolizumab)
#> Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
#> ℹ Please use `linewidth` instead.
#> ℹ The deprecated feature was likely used in the ggplot2 package.
#>   Please report the issue at <https://github.com/tidyverse/ggplot2/issues>.
#> Warning: Vectorized input to `element_text()` is not officially supported.
#> ℹ Results may be unexpected or may change in future versions of ggplot2.
#> Note: Very wide confidence intervals detected. X-axis capped for readability.
#> `height` was translated to `width`.


# Both adjusted and unadjusted
forestplotMV(glm_fit, data = pembrolizumab, include_unadjusted = TRUE)
#> Fitting univariate models for each predictor
#> Note: Adjusted model N=73 may differ from unadjusted model N=94 due to missing data in covariates
#> Warning: Vectorized input to `element_text()` is not officially supported.
#> ℹ Results may be unexpected or may change in future versions of ggplot2.
#> Note: Very wide confidence intervals detected. X-axis capped for readability.
#> `height` was translated to `width`.