aftreg {eha} | R Documentation

## Accelerated Failure Time Regression

### Description

The accelerated failure time model with parametric baseline hazard(s). Allows for stratification with different scale and shape in each stratum, and left truncated and right censored data.

### Usage

    aftreg(formula = formula(data), data = parent.frame(),
      na.action = getOption("na.action"), dist = "weibull", init, shape = 0,
      id, param = c("lifeAcc", "lifeExp"), control = list(eps = 1e-08, maxiter =
      20, trace = FALSE), singular.ok = TRUE, model = FALSE, x = FALSE,
      y = TRUE)

### Arguments

`formula` | a formula object, with the response on the left of a ~ operator, and the terms on the right. The response must be a survival object as returned by the Surv function.
`data` | a data.frame in which to interpret the variables named in the formula.
`na.action` | a missing-data filter function, applied to the model.frame, after any subset argument has been used. Default is `options()$na.action`.
`dist` | Which distribution? Default is "weibull", with the alternatives "gompertz", "ev", "loglogistic" and "lognormal". A special case like the `exponential` can be obtained by choosing "weibull" in combination with `shape = 1`.
`init` | vector of initial values of the iteration. Default initial value is zero for all variables.
`shape` | If positive, the shape parameter is fixed at that value. If zero or negative, the shape parameter is estimated. Stratification is now regarded as a meaningful option even if `shape` is fixed.
`id` | If there are more than one spell per individual, it is essential to keep spells together by the id argument. This allows for time-varying covariates.
`param` | Which parametrization should be used? The `lifeAcc` uses the parametrization given in the vignette, while the `lifeExp` uses the same as in the `survreg` function.
`control` | a list with components `eps` (convergence criterion), `maxiter` (maximum number of iterations), and `trace` (logical, debug output if `TRUE`). You can change any component without mention the other(s).
`singular.ok` | Not used.
`model` | Not used.
`x` | Return the design matrix in the model object?
`y` | Return the response in the model object?

### Details

The parameterization is different from the one used by `survreg`, when `param = "lifeAcc"`. The result is then true acceleration of time. Then the model is

S(t; a, b, β, z) = S_0((t / \exp(b - zβ))^{\exp(a)})

S(t; a, b, beta, z) = S_0((t/exp(b - z beta))^exp(a))

where S_0 is some standardized survivor function. The baseline parameters a and b are log shape and log scale, respectively. This is for the `default` parametrization. With the `lifeExp` parametrization, some signs are changed:

b - z beta

is changed to

b + z beta

. For the Gompertz distribution, the base parametrization is `canonical`, a necessity for consistency with the shape/scale paradigm (this is new in 2.3).

### Value

A list of class `c("aftreg", "coxreg")` with components

`coefficients` | Fitted parameter estimates.
`var` | Covariance matrix of the estimates.
`loglik` | Vector of length two; first component is the value at the initial parameter values, the second componet is the maximized value.
`score` | The score test statistic (at the initial value).
`linear.predictors` | The estimated linear predictors.
`means` | Means of the columns of the design matrix.
`w.means` | Weighted (against exposure time) means of covariates; weighted relative frequencies of levels of factors.
`n` | Number of spells in indata (possibly after removal of cases with NA's).
`events` | Number of events in data.
`terms` | Used by extractor functions.
`assign` | Used by extractor functions.

`wald.test` | The Wald test statistic (at the initial value).
`y` | The Surv vector.
`isF` | Logical vector indicating the covariates that are factors.
`covars` | The covariates.
`ttr` | Total Time at Risk.
`levels` | List of levels of factors.
`formula` | The calling formula.
`call` | The call.
`method` | The method.
`convergence` | Did the optimization converge?
`fail` | Did the optimization fail? (Is `NULL` if not).
`pfixed` | TRUE if shape was fixed in the estimation.
`param` | The parametrization.

### Author(s)

Göran Broström

### See Also

`coxreg`, `phreg`, `survreg`

### Examples

    data(mort)
    aftreg(Surv(enter, exit, event) ~ ses, param = "lifeExp", data = mort)

[Package eha version 2.6.0 Index]