  The main purpose of this paper is to introduce a new class of regression
models for bounded continuous data, commonly encountered in applied research.
The models, named the power logit regression models, assume that the response
variable follows a distribution in a wide, flexible class of distributions with
three parameters, namely the median, a dispersion parameter and a skewness
parameter. The paper offers a comprehensive set of tools for likelihood
inference and diagnostic analysis, and introduces the new R package PLreg.
Applications with real and simulated data show the merits of the proposed
models, the statistical tools, and the computational package.
