cmpp (version 0.0.1)

CIF_Figs: Plot Cumulative Incidence Functions (CIF) with Confidence Intervals

Description

This function plots the cumulative incidence functions (CIF) for two competing risks based on the estimated parameters and their variances. It includes confidence intervals for the CIFs.

Usage

CIF_Figs(initial_params, TimeFailure, OrderType = c(2, 1), RiskNames = NULL)

Value

A ggplot object showing the CIFs and their confidence intervals.

Arguments

initial_params

A numeric vector of initial parameter values to start the optimization.

TimeFailure

A numeric vector of failure times corresponding to observations.

OrderType

A numeric vector indicating the order of the competing risks. Default is c(2, 1).

RiskNames

A character vector of names for the competing risks. Default is NULL.

Details

This function performs the following steps:

• Estimates the model parameters using the estimate_parameters function.

• Computes the Hessian matrix using the compute_hessian function.

• Ensures that the diagonal elements of the covariance matrix are positive.

• Computes the cumulative incidence functions (CIF) for two competing risks.

• Plots the CIFs along with their confidence intervals.

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)
initial_params <- c(0.001, 0.001, 0.001, 0.001)
result <- CIF_res1(initial_params)
print(result)
initial_params <- c(0.01, 0.01, 0.01, 0.01)
TimeFailure <- seq(0, 10, by = 0.1)
plot <- CIF_Figs(initial_params, TimeFailure)
print(plot)