| PackageDescription | GNU R regression modeling strategies tools by Frank Harrell
Regression modeling, testing, estimation, validation, graphics, prediction,
and typesetting by storing enhanced model design attributes in the fit.
Design is a collection of about 180 functions that assist and streamline
modeling, especially for biostatistical and epidemiologic applications.
It also contains new functions for binary and ordinal logistic regression
models and the Buckley-James multiple regression model for right-censored
responses, and implements penalized maximum likelihood estimation for
logistic and ordinary linear models. Design works with almost any
regression model, but it was especially written to work with logistic
regression, Cox regression, accelerated failure time models, ordinary
linear models, and the Buckley-James model.
.
See Frank Harrell (2002), Regression Modeling Strategies, Springer
Series in Statistics, as well as
http://hesweb1.med.virginia.edu/biostat/s/Design.html |