print.additivePenal {frailtypack} | R Documentation |
Print a Short Summary of parameter estimates of an additive frailty model
Description
Prints a short summary of the parameter estimates of an additive frailty model or more generally of an 'additivePenal' object
Usage
## S3 method for class 'additivePenal':
print(x, digits = max(options()$digits - 4, 3), ...)
Arguments
x |
the result of a call to the additivePenal function |
digits |
number of digits to print |
... |
other unusued arguments |
Value
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 |
coef |
the coefficients of the linear predictor, which
multiply the columns of the model matrix. |
SE(H) |
the standard error deduced from the variance matrix of theta and of the coefficients. |
SE(HIH) |
the standard error deduced from the robust estimation of the variance matrix of theta and of the coefficients. |
z |
quantile of the \chi^2 mixture distribution |
p |
p-value |
Variance for the random intercept |
Variance for the random effect associated to the baseline risk functon |
Variance for the random slope |
Variance for the random effect associated to the treatment effects across trials |
See Also
summary.additivePenal
,
additivePenal
,
plot.additivePenal
Examples
# /*** Additive frailty model with 1 covariate ***/
## Not run:
data(dataAdditive)
modAdd<-additivePenal(Surv(t1,t2,event)~cluster(group)+var1+slope(var1),
correlation=TRUE,data=dataAdditive,n.knots=8,kappa1=862)
# It takes around 4 minutes to converge. 'var1' is boolean as a treatment variable. #
print(modAdd)
## End(Not run)
[Package
frailtypack version 2.2-12
Index]