Design: Design Package
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, the Buckley-James model, and generalized least squares
for serially or spatially correlated observations.
Downloads:
Reverse dependencies: