Cox Non-Proportional Hazards Model with Time-Varying Coefficients

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Documentation for package ‘surtvep’ version 1.0.0

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baseline calculating baseline hazard and baseline cumulative hazard using the result from a 'coxtv' or 'coxtp' object
confint.coxtp get confidence intervals of time-varying coefficients from a fitted object
confint.coxtv get confidence intervals of time-varying coefficients from a fitted object
coxtp fit a Cox non-proportional hazards model with P-spline or Smoothing-spline, with penalization tuning parameter chosen by information criteria or cross-validation
coxtv fit a Cox non-proportional hazards model
cv.coxtp fit a cross-validated Cox non-proportional hazards model with P-spline or Smoothing-spline where penalization tuning parameter is provided by cross-validation
ExampleData example data with 2000 observations of 2 continuous variables
ExampleDataBinary example data with 2000 observations of 2 binary variables
get.tvcoef helper function to get time-varying coefficients
IC calculating information criteria from a 'coxtp' object
plot.baseline plotting the baseline hazard
plot.coxtp plotting results from a fitted 'coxtp' object
plot.coxtv plotting results from a fitted 'coxtv' object
StrataExample example data for stratified model illustration
support Study to Understand Prognoses Preferences Outcomes and Risks of Treatment
tvef.ph testing the proportional hazards assumption from a 'coxtv' or 'coxtp' object
tvef.zero testing the significance of the covariates from a 'coxtv' or 'coxtp' object
tvef.zero.time testing the significance of the covariates from a 'coxtv' or 'coxtp' object using a Wald test statistic