Greg (version 2.0.2)

getModelData4Forestplot: Get model data

Description

A helper function for forestplotCombineRegrObj(). Extracts the data from the regression model fits and returns a list with model data gathered by the function [broom::tidy()]

Usage

getModelData4Forestplot(
  regr.obj,
  exp = TRUE,
  variablesOfInterest.regexp = NULL,
  add_first_as_ref = FALSE
)

Arguments

regr.obj

A list with all the fits that have variables that are to be identified through the regular expression

exp

Report in exponential form. Default true since the function was built for use with survival models.

variablesOfInterest.regexp

A regular expression identifying the variables that are of interest of comparing. For instance it can be "(score|index|measure)" that finds scores in different models that should be compared.

add_first_as_ref

If you want that the first variable should be reference for that group of variables. The ref is a variable with the estimate 1 or 0 depending if exp() and the confidence interval 0.

Examples

org.par <- par("ask" = TRUE)

# simulated data to test
library(tidyverse)
set.seed(10)
cov <- tibble(ftime = rexp(200),
              fstatus = sample(0:1, 200, replace = TRUE),
              x1 = runif(200),
              x2 = runif(200),
              x3 = runif(200)) |> 
  # Add some column labels
  Gmisc::set_column_labels(x1 = "First variable",
                           x2 = "Second variable")

library(rms)
ddist <- datadist(cov)
options(datadist = "ddist")

fit1 <- cph(Surv(ftime, fstatus) ~ x1 + x2, data = cov)
fit2 <- cph(Surv(ftime, fstatus) ~ x1 + x3, data = cov)

list(`First model` = fit1, 
     `Second model` = fit2) |> 
  forestplotCombineRegrObj(variablesOfInterest.regexp = "(x2|x3)") |> 
  fp_set_style(lines = "steelblue",
               box = "darkblue")

# How to add expressions to the plot label
list(fit1, fit2) |> 
  forestplotCombineRegrObj(variablesOfInterest.regexp = "(x2|x3)",
                           reference.names = c("First model", "Second model"),
                           post_process_data = \(data) {
                             data$column_label[4] <- c(rlang::expr(expression(Fever >= 38.5)))
                             return(data)
                           })

par(org.par)