Cure models for analyzing survival data with a cured fraction of long-term survivors. Implements mixture cure models and non-mixture cure models for oncology research.
Usage
curemodels(
data,
time,
status,
predictors,
model_type = "mixture",
cure_link = "logit",
survival_dist = "weibull",
bootstrap_ci = FALSE,
n_bootstrap = 1000,
cure_threshold = 60,
plot_cure_fraction = TRUE,
plot_survival = TRUE,
goodness_of_fit = TRUE,
sensitivity_analysis = FALSE
)Arguments
- data
The data as a data frame.
- time
Follow-up time variable
- status
Event status variable
- predictors
Predictor variables for the model
- model_type
Type of cure model: mixture, non-mixture, or both
- cure_link
Link function for the cure probability model
- survival_dist
Distribution for modeling survival of uncured patients
- bootstrap_ci
Use bootstrap for confidence interval estimation
- n_bootstrap
Number of bootstrap samples
- cure_threshold
Time threshold for defining cured patients
- plot_cure_fraction
Generate cure fraction plot
- plot_survival
Generate survival curve plots
- goodness_of_fit
Conduct goodness of fit assessment
- sensitivity_analysis
Conduct sensitivity analysis
Value
A results object containing:
results$todo | a html | ||||
results$warnings | a html | ||||
results$summary | a html | ||||
results$modelTable | a table | ||||
results$cureTable | a table | ||||
results$cureFractionPlot | an image | ||||
results$survivalPlot | an image | ||||
results$goodnessOfFit | a table | ||||
results$sensitivityAnalysis | a html | ||||
results$modelComparison | a table | ||||
results$interpretation | a html |
Tables can be converted to data frames with asDF or as.data.frame. For example:
results$modelTable$asDF
as.data.frame(results$modelTable)
Examples
# \donttest{
# Example usage
curemodels(
data = cancer_data,
time = followup_time,
status = death_status,
predictors = c(age, stage, treatment),
model_type = "mixture"
)
# }