multivariate_forest: Multivariate Plotter for Cox Regression

In WillFox/clinicalParser: Clinical Parser

Description

This function takes a data frame and performs Multivariate cox regression, prints a forrest plot, and returns a table that can use code from cox_univariate_plotter to customize the plot.

Usage

multivariate_forest(data, columns_to_test = c(), time = "TIME",
  outcome = "OUTCOME", title = "Forest Plot for Hazard",
  keep_insignificant = TRUE, show_only = c(), verbose = T)

Arguments

data	A data frame that contains an outcome column, time column, and a column name within columns_to_test.
columns_to_test	The columns to test from the data, if NONE, all columns are included
time	The continuous time to event column for the regression analysis. Default: "TIME"
outcome	The binary outcome column of the data. Default: "OUTCOME"
title	Title at top of plot. Default: "Forest Plot for Hazard"
keep_insignificant	When FALSE, p value greater than 0.05 are not included in the output, but remain in calculation. With TRUE, all variables remain shown. Default: TRUE
show_only	A vector of the variables to show in output. If empty vector, all are shown. Default: c()
verbose	the amount of status log output provided. Default: TRUE

Examples

multivariate_forest()

WillFox/clinicalParser documentation built on May 5, 2019, 1:33 a.m.