cmpp (version 0.0.1)

FineGray_Model: Fine-Gray Model for Competing Risks Data

Description

This function fits a Fine-Gray model for competing risks data using the cmprsk package. It estimates the subdistribution hazard model parameters, computes cumulative incidence functions (CIFs), and provides a summary of the results along with a plot of the CIFs.

Usage

FineGray_Model(CovarNames = NULL, Failcode = 1, RiskNames = NULL)

Value

A list containing:

Results

A summary of the Fine-Gray model fit.

Plot

A ggplot object showing the cumulative incidence functions (CIFs) for the competing risks.

CIF_Results

A data frame containing the CIFs for the competing risks, along with their corresponding time points.

Arguments

CovarNames

A character vector of names for the covariates. If NULL, default names will be generated.

Failcode

An integer specifying the event of interest (default is 1).

RiskNames

A character vector specifying the names of the competing risks. If NULL, default names ("Risk1" and "Risk2") will be used.

Details

This function retrieves the data initialized in the Cmpp model using the GetData function. It uses the crr function from the cmprsk package to fit the Fine-Gray model for competing risks. The function also computes cumulative incidence functions (CIFs) using the cuminc function and generates a plot of the CIFs for the competing risks.

Examples

library(cmpp)
data("fertility_data")
Nam <- names(fertility_data)
fertility_data$Education
datt <- make_Dummy(fertility_data, features = c("Education"))
datt <- datt$New_Data 
datt['Primary_Secondary'] <- datt$`Education:2`
datt['Higher_Education'] <- datt$`Education:3`
datt$`Education:2` <- datt$`Education:3` <- NULL
datt2 <- make_Dummy(datt, features = 'Event')$New_Data
d1 <- datt2$`Event:2`
d2 <- datt2$`Event:3`
feat <- datt2[c('age', 'Primary_Secondary', 'Higher_Education')] |> 
   data.matrix()
timee <- datt2[['time']]
Initialize(feat, timee, d1, d2, 1e-10)
result <- FineGray_Model(
  CovarNames = c("Covar1", "Covar2", "Covar3"),
  Failcode = 1,
  RiskNames = c("Event1", "Event2")
)
print(result$Results)  # Summary of the Fine-Gray model
#print(result$Plot)     # Plot of the CIFs
print(result$CIF_Results)  # CIF data