CIF_Figs {cmpp} | R Documentation |
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)
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 |
RiskNames |
A character vector of names for the competing risks. Default is |
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.
Value
A ggplot object showing the CIFs and 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)