select.parfm: AIC and BIC values of several Parametric Frailty Models
In parfm: Parametric Frailty Models

select.parfm

R Documentation

AIC and BIC values of several Parametric Frailty Models

Description

The function select.parfm() computes the AIC and BIC values of parametric frailty models with different baseline hazards and different frailty distributions.

Usage

select.parfm(formula, cluster=NULL, strata=NULL, data, inip=NULL, iniFpar=NULL,
             dist=c("exponential", "weibull", "inweibull", "frechet", "gompertz", 
                    "loglogistic", "lognormal", "logskewnormal"),
             frailty=c("none", "gamma", "ingau", "possta", "lognormal"),
             method="BFGS", maxit=500, Fparscale=1, correct=0)

Arguments

`formula`	A `formula` object, with the response on the left of a ~ operator, and the terms on the right. The response must be a survival object as returned by the `Surv` function.
`cluster`	The name of a cluster variable in data.
`strata`	The name of a strata variable in data.
`data`	A `data.frame` in which to interpret the variables named in the formula.
`inip`	The vector of initial values. First components are for the baseline hazard parameters according to the order given in 'details'; Other components are for the regression parameters according to the order given in 'formula'.
`iniFpar`	The initial value of the frailty parameter.
`dist`	The vector of baseline hazards' names. It can include any of `weibull`, `inweibull` (alias `frechet`), `exponential`, `gompertz`, `loglogistic` or `lognormal`.
`frailty`	The vector of frailty distributions' names. It can include any of: `none`, `gamma`, `ingau`, `possta` or `lognormal`.
`method`	The optimisation method from the function `optim()`.
`maxit`	Maximum number of iterations (see `optim()`).
`Fparscale`	the scaling value for the frailty parameter in `optim()`. Optimisation is performed on Fpar/Fparscale.
`correct`	A correction factor that does not change the marginal log-likelihood except for an additive constant given by #clusters * correct * log(10). It may be useful in order to get finite log-likelihood values in case of many events per cluster with Positive Stable frailties. Note that the value of the log-likelihood in the output is the re-adjusted value.

Value

An object of class select.parfm.

Author(s)

Federico Rotolo [aut, cre], Marco Munda [aut], Andrea Callegaro [ctb]

References

Munda M, Rotolo F, Legrand C (2012). parfm: Parametric Frailty Models in R. Journal of Statistical Software, 51(11), 1-20. DOI <\Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v051.i11")}>

Examples


data(kidney)
kidney$sex <- kidney$sex - 1

models <- select.parfm(Surv(time,status) ~ sex + age, 
                       dist = c("exponential", 
                                "weibull",
                                "inweibull",
                                "loglogistic", 
                                "lognormal", 
                                "logskewnormal"),
                       frailty = c("gamma", 
                                   "ingau", 
                                   "possta", 
                                   "lognormal"),
                       cluster = "id", data = kidney)
models
plot(models)

parfm documentation built on Aug. 8, 2025, 7:30 p.m.