twostageMLE: Twostage survival model fitted by pseudo MLE

In mets: Analysis of Multivariate Event Times

Twostage survival model fitted by pseudo MLE

Description

Fits Clayton-Oakes clustered survival data using marginals that are on Cox form in the likelihood for the dependence parameter as in Glidden (2000). The dependence can be modelled via a

1. Regression design on dependence parameter.

We allow a regression structure for the indenpendent gamma distributed random effects and their variances that may depend on cluster covariates. So

\theta = h( z_j^T \alpha)

where z is specified by theta.des . The link function can be the exp when var.link=1

Usage

twostageMLE(
  margsurv,
  data = parent.frame(),
  theta = NULL,
  theta.des = NULL,
  var.link = 0,
  method = "NR",
  no.opt = FALSE,
  weights = NULL,
  se.cluster = NULL,
  ...
)

Arguments

margsurv	Marginal model from phreg
data	data frame
theta	Starting values for variance components
theta.des	design for dependence parameters, when pairs are given this is could be a (pairs) x (numer of parameters) x (max number random effects) matrix
var.link	Link function for variance if 1 then uses exp link
method	type of opitmizer, default is Newton-Raphson "NR"
no.opt	to not optimize, for example to get score and iid for specific theta
weights	cluster specific weights, but given with length equivalent to data-set, weights for score equations
se.cluster	specifies how the influence functions are summed before squared when computing the variance. Note that the id from the marginal model is used to construct MLE, and then these scores can be summed with the se.cluster argument.
...	arguments to be passed to optimizer

Author(s)

Thomas Scheike

References

Measuring early or late dependence for bivariate twin data Scheike, Holst, Hjelmborg (2015), LIDA

Twostage modelling of additive gamma frailty models for survival data. Scheike and Holst, working paper

Shih and Louis (1995) Inference on the association parameter in copula models for bivariate survival data, Biometrics, (1995).

Glidden (2000), A Two-Stage estimator of the dependence parameter for the Clayton Oakes model, LIDA, (2000).

Examples

data(diabetes)
dd <- phreg(Surv(time,status==1)~treat+cluster(id),diabetes)
oo <- twostageMLE(dd,data=diabetes)
summary(oo)

theta.des <- model.matrix(~-1+factor(adult),diabetes)

oo <-twostageMLE(dd,data=diabetes,theta.des=theta.des)
summary(oo)

mets documentation built on May 29, 2024, 3:51 a.m.