  Transformation models provide a common tool for regression analysis of
censored failure time data. The most common approach towards parameter
estimation in these models is based on the nonparametric profile likelihood
method. Several authors proposed also ad hoc M-estimators of the Euclidean
component of the model. These estimators are usually simpler to impelement and
many of them have good practical performance. In this paper we consider the
form of the information bound for estimation if the Euclidean parameter of the
model and propose a modification of inefficient M-estimators to one-step
maximum likelihood estimates.
