# aftreg {eha}

### 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

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).

### Values

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.
- 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.

Documentation reproduced from package eha, version 2.4-1. License: GPL (>= 3)