Description Usage Arguments Details Value Note Author(s) References See Also Examples
Runs the survival analysis with several useful options, using either MLE (via flexsurv) or a Bayesian approach (via RINLA or rstan)
1 
formula 
a formula specifying the model to be used, in the form

data 
A data frame containing the data to be used for the analysis.
This must contain data for the 'event' variable. In case there is no
censoring, then 
distr 
a (vector of) string(s) containing the name(s) of the model(s) to be fitted. Available options are:

method 
A string specifying the inferential method ( 
... 
Additional options (for INLA or HMC). **INLA** specific options **HMC** specific options 
On object in the class survHE
containing the following elements
models 
A list containing the fitted models. These contain
the output from the original inference engine ( 
model.fitting 
A list containing the output of the modelfit statistics (AIC, BIC, DIC). The AIC and BIC are estimated for all methods, while the DIC is only estimated when using Bayesian inference. 
method 
A string indicating the method used to
fit the model, ie 
misc 
A list containing the time needed to run the model(s) (in
seconds), the formula used, the results of the KaplanMeier analysis (which
is automatically performed using 
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Gianluca Baio
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30  # Loads an example dataset from 'flexsurv'
data(bc)
# Fits the same model using the 3 inference methods
mle = fit.models(formula=Surv(recyrs,censrec)~group,data=bc,
distr="exp",method="mle")
inla = fit.models(formula=Surv(recyrs,censrec)~group,data=bc,
distr="exp",method="inla")
hmc = fit.models(formula=Surv(recyrs,censrec)~group,data=bc,
distr="exp",method="hmc")
# Prints the results in comparable fashion using the survHE method
print(mle)
print(inla)
print(hmc)
# Or visualises the results using the original packages methods
print(mle,original=TRUE)
print(inla,original=TRUE)
print(hmc,original=TRUE)
# Plots the survival curves and estimates
plot(mle)
plot(mle,inla,hmc,labs=c("MLE","INLA","HMC"),colors=c("black","red","blue"))

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