Implements rank-based accelerated failure time (AFT) models using generalized estimating equations (GEE) for survival data analysis. This approach provides robust estimation when proportional hazards assumptions are violated, offering distribution-free methods for modeling survival times with emphasis on median survival relationships and time acceleration effects in clinical research applications.
Usage
raftgee(
data,
elapsedtime,
outcome,
covariates,
outcomeLevel = "1",
rank_method = "logrank",
correlation_structure = "independence",
cluster_variable,
confidence_level = 0.95,
max_iterations = 100,
convergence_tolerance = 1e-06,
weights_variable,
robust_variance = TRUE,
bootstrap_samples = 0,
show_model_summary = TRUE,
show_coefficients = TRUE,
show_diagnostics = TRUE,
show_residual_plots = TRUE,
show_qq_plots = TRUE,
show_survival_plots = TRUE,
show_acceleration_plots = TRUE,
show_comparison_plots = TRUE,
showSummaries = FALSE,
showExplanations = FALSE
)Arguments
- data
the data as a data frame
- elapsedtime
Survival time or follow-up duration variable
- outcome
Event indicator variable (0/1, FALSE/TRUE, or factor)
- covariates
Covariate variables for AFT modeling
- outcomeLevel
Level of outcome variable indicating event occurrence
- rank_method
Rank-based test method for AFT estimation
- correlation_structure
Working correlation structure for GEE
- cluster_variable
Variable defining clusters for correlated observations
- confidence_level
Confidence level for parameter estimates
- max_iterations
Maximum number of iterations for GEE algorithm
- convergence_tolerance
Convergence tolerance for parameter estimation
- weights_variable
Optional weights variable for observations
- robust_variance
Use robust sandwich variance estimator
- bootstrap_samples
Number of bootstrap samples for variance estimation (0 = no bootstrap)
- show_model_summary
Display comprehensive AFT model summary
- show_coefficients
Display AFT model coefficients table
- show_diagnostics
Display model diagnostic statistics
- show_residual_plots
Display residual diagnostic plots
- show_qq_plots
Display quantile-quantile plots
- show_survival_plots
Display AFT-based survival curves
- show_acceleration_plots
Display time acceleration factor plots
- show_comparison_plots
Display comparison with Cox models
- showSummaries
Generate natural language summaries of the analysis results
- showExplanations
Show detailed explanations of the methodology and interpretation
Value
A results object containing:
results$modelSummary | a table | ||||
results$coefficients | a table | ||||
results$diagnostics | a table | ||||
results$geeDiagnostics | a table | ||||
results$convergenceInfo | a table | ||||
results$modelComparison | a table | ||||
results$residualPlots | an image | ||||
results$qqPlots | an image | ||||
results$survivalPlots | an image | ||||
results$accelerationPlots | an image | ||||
results$comparisonPlots | an image | ||||
results$correlationPlots | an image | ||||
results$summaryTable | a html | ||||
results$methodExplanation | a html |
Tables can be converted to data frames with asDF or as.data.frame. For example:
results$modelSummary$asDF
as.data.frame(results$modelSummary)