Fitting and testing tobit regression models for censored data.
Usage
tobit(formula, left = 0, right = Inf, dist = "gaussian",
subset = NULL, data = list(), ...)
Arguments
formula
a symbolic description of a regression model of type
y ~ x1 + x2 + ....
left
left limit for the censored dependent variable y.
If set to -Inf, y is assumed not to be left-censored.
right
right limit for the censored dependent variable y.
If set to Inf, the default, y is assumed not to be right-censored.
dist
assumed distribution for the dependent variable y.
This is passed to survreg, see the respective man page for
more details.
subset
a specification of the rows to be used.
data
a data frame containing the variables in the model.
...
further arguments passed to survreg.
Details
The function tobit is a convenience interface to survreg
(for survival regression, including censored regression) setting different
defaults and providing a more convenient interface for specification
of the censoring information.
The default is the classical tobit model (Tobin 1958, Greene 2003) assuming
a normal distribution for the dependent variable with left-censoring at 0.
Technically, the formula of type y ~ x1 + x2 + ... passed to tobit
is simply transformed into a formula suitable for survreg: This means
the dependent variable is first censored and then wrapped into a Surv
object containing the censoring information which is subsequently passed to
survreg, e.g., Surv(ifelse(y <= 0, 0, y), y > 0, type = "left") ~ x1 + x2 + ...
for the default settings.
Value
An object of class "tobit" inheriting from class "survreg".