print.jointPenal {frailtypack} | R Documentation |
Prints a short summary of parameter estimates of a joint frailty model, or more generally an object of class 'frailtyPenal' for joint frailty models.
## S3 method for class 'jointPenal': print(x, digits = max(options()$digits - 4, 3), ...)
x |
the result of a call to the jointPenal function |
digits |
number of digits to print |
... |
other unusued arguments |
Print, separately for each type of event (recurrent and terminal), the parameter estimates of the survival or hazard functions.
n |
the number of observations used in the fit. |
n.groups |
the maximum number of groups used in the fit |
n.events |
the number of events observed in the fit |
theta |
variance of the common frailty term |
alpha |
the coefficient associated with the frailty parameter terminal event hazard function |
coef |
the coefficients of the linear predictor, which multiply the columns of the model matrix. |
varH |
the variance matrix of theta and of the coefficients. |
varHIH |
the robust estimation of the variance matrix of theta and of the coefficients. |
SE(H) |
the standard error of the estimaes deduced from the variance matrix of theta and of the coefficients. |
SE(HIH) |
the standard error of the estimaes deduced from the robust estimation of the variance matrix of theta and of the coefficients. |
p |
p-value |
summary.jointPenal
, frailtyPenal for Joint frailty models
,plot.jointPenal
# /*** Joint frailty model ***/ ## Not run: data(readmission) ## Gap-time ## modJoint_gap<-frailtyPenal(Surv(time,event)~cluster(id)+sex+as.factor(dukes) +as.factor(charlson)+terminal(death), formula.terminalEvent=~sex+as.factor(dukes)+as.factor(charlson), data=readmission,n.knots=14,kappa1=9550000000, kappa2=1410000000000,Frailty=TRUE,joint=TRUE,recurrentAG=FALSE) # It takes around 1 minute to converge.# print(modJoint_gap) ## End(Not run)