FineGray_Model {cmpp} | R Documentation |
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)
Arguments
CovarNames |
A character vector of names for the covariates. If |
Failcode |
An integer specifying the event of interest (default is |
RiskNames |
A character vector specifying the names of the competing risks. If |
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.
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. |
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