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IPCW Estimator for Recurrent Events

Source: R/recreg.R
recregIPCW.Rd

Computes the Inverse Probability of Censoring Weighted (IPCW) estimator for the mean number of recurrent events. Supports various estimators including the Ghosh-Lin and Lawless-Cook estimators.

Usage

recregIPCW(
  formula,
  data = data,
  cause = 1,
  cens.code = 0,
  death.code = 2,
  cens.model = ~1,
  km = TRUE,
  times = NULL,
  beta = NULL,
  offset = NULL,
  type = c("II", "I"),
  marks = NULL,
  weights = NULL,
  model = c("exp", "lin"),
  no.opt = FALSE,
  augmentation = NULL,
  method = "nr",
  se = TRUE,
  ...
)

Arguments

formula

Formula with an 'Event' outcome.

data

Data frame.

cause

Cause of interest (default is 1).

cens.code

Censoring code (default is 0).

death.code

Death code (default is 2).

cens.model

Formula for the censoring model (default is ~1).

km

Logical; if TRUE, uses Kaplan-Meier for censoring weights; otherwise uses Cox model.

times

Time points for estimation (required).

beta

Initial values for coefficients (optional).

offset

Offsets.

type

Type of estimator: "II" (default) or "I".

marks

Mark values.

weights

Weights.

model

Model type for the mean: "exp" (default) or "lin".

no.opt

Logical; if TRUE, skips optimization.

augmentation

Augmentation terms.

method

Optimization method (default is "nr").

se

Logical; if TRUE, computes standard errors.

...

Additional arguments.

Value

An object of class "binreg" (extending "resmean") containing:

coef

Estimated coefficients.

var

Variance-covariance matrix.

iid

Influence functions.

times

Time points.

Y

Observed counts.

See also

recreg

Author

Thomas Scheike