Smooth Survival Models, Including Generalized Survival Models

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Documentation for package ‘rstpm2’ version 1.6.3

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addModel Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
aft Parametric accelerated failure time model with smooth time functions
aft-class Class "stpm2" ~~~
aftModel Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
AIC-method Class "pstpm2"
AICc-method Class "pstpm2"
anova-method Class "pstpm2"
as.data.frame.markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
as.data.frame.markov_msm_diff Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
as.data.frame.markov_msm_ratio Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
as.data.frame.markov_sde Predictions for continuous time, nonhomogeneous Markov multi-state models using Aalen's additive hazards models.
bhazard Placemarker function for a baseline hazard function.
BIC-method Class "pstpm2"
brcancer German breast cancer data from Stata.
coef<- Generic method to update the coef in an object.
collapse_markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
colon Colon cancer.
confint.predictnl Estimation of standard errors using the numerical delta method.
cox.tvc Test for a time-varying effect in the 'coxph' model
diff Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
diff.markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
eform S3 method for to provide exponentiated coefficents with confidence intervals.
eform-method Class "pstpm2"
eform-method Class "stpm2" ~~~
eform.default S3 method for to provide exponentiated coefficents with confidence intervals.
eform.stpm2 S3 method for to provide exponentiated coefficents with confidence intervals.
grad gradient function (internal function)
gsm Parametric and penalised generalised survival models
gsm.control Defaults for the gsm call
gsm_design Extract design information from an stpm2/gsm object and newdata for use in C++
hazFun Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
hrModel Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
incrVar Utility that returns a function to increment a variable in a data-frame.
legendre.quadrature.rule.200 Legendre quadrature rule for n=200.
lhs Internal functions for the rstpm2 package.
lhs<- Internal functions for the rstpm2 package.
lines-method Class "pstpm2"
lines-method Class "stpm2" ~~~
lines.pstpm2 S3 methods for lines
lines.stpm2 S3 methods for lines
markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
markov_sde Predictions for continuous time, nonhomogeneous Markov multi-state models using Aalen's additive hazards models.
nsx Generate a Basis Matrix for Natural Cubic Splines (with eXtensions)
nsxD Generate a Basis Matrix for the first derivative of Natural Cubic Splines (with eXtensions)
numDeltaMethod Calculate numerical delta method for non-linear predictions.
plot-method Class "stpm2" ~~~
plot-method plots for an stpm2 fit
plot-method Class "pstpm2"
plot-method Class "stpm2" ~~~
plot-method Class '"tvcCoxph"'
plot-methods plots for an stpm2 fit
plot.markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
plot.markov_sde Predictions for continuous time, nonhomogeneous Markov multi-state models using Aalen's additive hazards models.
popmort Background mortality rates for the colon dataset.
predict-method Class "stpm2" ~~~
predict-method Predicted values for an stpm2 or pstpm2 fit
predict-methods Predicted values for an stpm2 or pstpm2 fit
predict.formula Estimation of standard errors using the numerical delta method.
predict.nsx Evaluate a Spline Basis
predictnl Estimation of standard errors using the numerical delta method.
predictnl-method Class "stpm2" ~~~
predictnl-method ~~ Methods for Function predictnl ~~
predictnl-method Class "pstpm2"
predictnl-method Class "stpm2" ~~~
predictnl-methods ~~ Methods for Function predictnl ~~
predictnl.default Estimation of standard errors using the numerical delta method.
predictnl.lm Estimation of standard errors using the numerical delta method.
print.predictnl Estimation of standard errors using the numerical delta method.
pstpm2 Parametric and penalised generalised survival models
pstpm2-class Class "pstpm2"
qAICc-method Class "pstpm2"
ratio_markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
rbind.markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
residuals-method Residual values for an stpm2 or pstpm2 fit
residuals-methods Residual values for an stpm2 or pstpm2 fit
rhs Internal functions for the rstpm2 package.
rhs<- Internal functions for the rstpm2 package.
simulate-method Simulate values from an stpm2 or pstpm2 fit
simulate-methods Simulate values from an stpm2 or pstpm2 fit
smoothpwc Utility to use a smooth function in markov_msm based on piece-wise constant values
splineFun Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
standardise Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
standardise.markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
standardise.markov_sde Predictions for continuous time, nonhomogeneous Markov multi-state models using Aalen's additive hazards models.
stpm2 Parametric and penalised generalised survival models
stpm2-class Class "stpm2" ~~~
subset.markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
summary-method Class "pstpm2"
summary-method Class "stpm2" ~~~
transform.markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
tvcCoxph-class Class '"tvcCoxph"'
update-method Methods for Function update
update-methods Methods for Function update
vcov.markov_msm Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.
voptimise Vectorised One Dimensional Optimization
voptimize Vectorised One Dimensional Optimization
vuniroot Vectorised One Dimensional Root (Zero) Finding
zeroModel Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models.