frailtypack (version 2.2-13)

print.jointPenal: Print a Short Summary of parameter estimates of a joint frailty model

Description

Prints a short summary of parameter estimates of a joint frailty model, or more generally an object of class 'frailtyPenal' for joint frailty models.

Usage

## S3 method for class 'jointPenal':
print(x, digits = max(options()$digits - 4, 3), ...)

Arguments

x

the result of a call to the jointPenal function

digits

number of digits to print

...

other unusued arguments

Value

• 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

See Also

summary.jointPenal, frailtyPenal for Joint frailty models,plot.jointPenal

Examples

# /*** Joint frailty model ***/
 

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)