emfrail_dist: Distribution parameters for emfrail

Description Usage Arguments Details Value See Also Examples

View source: R/emfrail_arguments.R

Description

Distribution parameters for emfrail

Usage

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emfrail_dist(dist = "gamma", theta = 2, pvfm = -1/2,
  left_truncation = FALSE, basehaz = "breslow")

Arguments

dist

One of 'gamma', 'stable' or 'pvf'.

theta

A starting value for the 'outer' maximization with respect to the frailty parameter θ. Must be >0.

pvfm

Only relevant if dist = 'pvf' is used. It determines which PVF distribution should be used. Must be larger than -1 and not equal to 0.

left_truncation

Logical. Whether the data set represents left truncated survival times.

basehaz

A character string which determines how the baseline hazard is calculated. The default is "breslow", but other possible options are "weibull", "exponential" "gaussian", "logistic", "lognormal" or "loglogistic".

Details

The theta argument must be positive. In the case of gamma or PVF, this is the inverse of the frailty variance, i.e. the larger the theta is, the closer the model is to a Cox model. When dist = "pvf" and pvfm = -0.5, the inverse Gaussian distribution is obtained. For the positive stable distribution, the γ parameter of the Laplace transform is θ / (1 + θ), with the alpha parameter fixed to 1.

Value

An object of the type emfrail_dist, which is mostly used to denote the supported frailty distributions in a consistent way.

See Also

emfrail, emfrail_control

Examples

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emfrail_dist()
# Compound Poisson distribution:
emfrail_dist(dist = 'pvf', theta = 1.5, pvfm = 0.5)
# Inverse Gaussian distribution:
emfrail_dist(dist = 'pvf')

Example output

Loading required package: survival
$dist
[1] "gamma"

$theta
[1] 2

$pvfm
[1] -0.5

$left_truncation
[1] FALSE

attr(,"class")
[1] "emfrail_dist"
$dist
[1] "pvf"

$theta
[1] 1.5

$pvfm
[1] 0.5

$left_truncation
[1] FALSE

attr(,"class")
[1] "emfrail_dist"
$dist
[1] "pvf"

$theta
[1] 2

$pvfm
[1] -0.5

$left_truncation
[1] FALSE

attr(,"class")
[1] "emfrail_dist"

frailtyEM documentation built on Sept. 22, 2019, 5:05 p.m.