select.parfm | R Documentation |
The function select.parfm()
computes the AIC and BIC values
of parametric frailty models with different baseline hazards and different frailty distributions.
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)
formula |
A |
cluster |
The name of a cluster variable in data. |
strata |
The name of a strata variable in data. |
data |
A |
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 |
frailty |
The vector of frailty distributions' names.
It can include any of: |
method |
The optimisation method from the function |
maxit |
Maximum number of iterations (see |
Fparscale |
the scaling value for the frailty parameter in |
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. |
An object of class select.parfm
.
Federico Rotolo [aut, cre], Marco Munda [aut], Andrea Callegaro [ctb]
Munda M, Rotolo F, Legrand C (2012). parfm: Parametric Frailty Models in R. Journal of Statistical Software, 51(11), 1-20. DOI <doi: 10.18637/jss.v051.i11>
parfm
,
ci.parfm
,
predict.parfm
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)
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