anova.parfm: Analysis of Deviance for a parametric frailty model.

Description Usage Arguments Details Value Warning Author(s) References See Also Examples

View source: R/anova.parfm.R

Description

Compute an analysis of deviance table for one or more parametric frailty model fits.

Usage

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## S3 method for class 'parfm'
anova(object, ...)

Arguments

object

An object of class parfm

...

Further parfm objects

Details

Specifying a single object gives a sequential analysis of deviance table for that fit. That is, the reductions in the model log-likelihood as each term of the formula is added in turn are given in as the rows of a table, plus the log-likelihoods themselves.

If more than one object is specified, the table has a row for the degrees of freedom and loglikelihood for each model. For all but the first model, the change in degrees of freedom and loglik is also given. (This only make statistical sense if the models are nested.) It is conventional to list the models from smallest to largest, but this is up to the user.

The table contains test statistics (and P values) comparing the reduction in loglik for each row.

Value

An object of class "anova" inheriting from class "data.frame".

Warning

The comparison between two or more models by anova will only be valid if they are fitted to the same dataset. This may be a problem if there are missing values.

Author(s)

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

References

Marco Munda, Federico Rotolo, Catherine Legrand (2012). parfm: Parametric Frailty Models in R. Journal of Statistical Software, 51(11), 1-20. URL http://www.jstatsoft.org/v51/i11/.

See Also

parfm, anova.

Examples

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fit <- parfm(formula = Surv(time, status) ~ sex + age, cluster = "id",
             data = kidney, dist = "exponential", frailty = "gamma")
anova(fit)
fit2 <- parfm(formula = Surv(time, status) ~ sex, cluster = "id",
              data = kidney, dist = "exponential", frailty = "gamma")
anova(fit2, fit)

parfm documentation built on May 31, 2017, 2:48 a.m.