Time-updated survival estimates using time-varying regression coefficients and dynamic hazard functions. Incorporates real-time patient information updates for precision medicine and personalized survival prediction.
Usage
timeupdatesurvival(
data,
time,
status,
covariates,
id,
update_times = "0.5, 1, 2, 5",
method = "aalen_additive",
smoothing_method = "lowess",
bandwidth = 0.5,
degrees_freedom = 4,
confidence_level = 0.95,
prediction_horizon = 5,
bootstrap_samples = 200,
include_residuals = TRUE,
dynamic_prediction = TRUE,
individual_profiles = FALSE,
significance_testing = TRUE,
model_comparison = TRUE
)Arguments
- data
the data as a data frame
- time
Time-to-event or follow-up time variable (numeric)
- status
Event indicator variable (1/TRUE = event occurred, 0/FALSE = censored)
- covariates
Covariates for time-varying coefficient analysis
- id
Subject identifier for longitudinal data and repeated measurements
- update_times
Comma-separated list of time points for coefficient updates (e.g., "0.5, 1, 2, 5")
- method
Method for estimating time-varying regression coefficients
- smoothing_method
Smoothing method for time-varying coefficient estimation
- bandwidth
Bandwidth parameter for smoothing (0.1 to 2.0)
- degrees_freedom
Degrees of freedom for spline-based methods
- confidence_level
Confidence level for confidence bands
- prediction_horizon
Time horizon for dynamic survival predictions
- bootstrap_samples
Number of bootstrap samples for confidence band estimation
- include_residuals
Include residual analysis and model diagnostics
- dynamic_prediction
Enable dynamic survival prediction with updated coefficients
- individual_profiles
Generate individual-level time-varying coefficient profiles
- significance_testing
Perform tests for time-varying coefficients vs. constant coefficients
- model_comparison
Compare time-varying models with standard Cox regression
Value
A results object containing:
results$instructions | a html | ||||
results$modelSummary | a table | ||||
results$timeVaryingCoefficients | a table | ||||
results$cumulativeCoefficients | a table | ||||
results$dynamicPredictions | a table | ||||
results$significanceTests | a table | ||||
results$modelComparison | a table | ||||
results$residualAnalysis | a table | ||||
results$goodnessOfFit | a table | ||||
results$timeVaryingPlot | an image | ||||
results$cumulativePlot | an image | ||||
results$dynamicPredictionPlot | an image | ||||
results$residualPlots | an image | ||||
results$smoothingDiagnostics | an image | ||||
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)