Fitting and testing tobit regression models for censored data.
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 + ...