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OrdFacReg (version 1.0.6)

Least Squares, Logistic, and Cox-Regression with Ordered Predictors

Description

In biomedical studies, researchers are often interested in assessing the association between one or more ordinal explanatory variables and an outcome variable, at the same time adjusting for covariates of any type. The outcome variable may be continuous, binary, or represent censored survival times. In the absence of a precise knowledge of the response function, using monotonicity constraints on the ordinal variables improves efficiency in estimating parameters, especially when sample sizes are small. This package implements an active set algorithm that efficiently computes such estimators.

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Version

Install

install.packages('OrdFacReg')

Monthly Downloads

180

Version

1.0.6

License

GPL (>= 2)

Maintainer

Last Published

July 4th, 2015

Functions in OrdFacReg (1.0.6)

ordFacRegCox

Compute Cox-regression for ordered predictors
internal

Internal functions for ordered factor regression functions
ordFacReg

Compute least squares or logistic regression for ordered predictors
OrdFacReg-package

Least Squares, Logistic, and Cox-Regression with Ordered Predictors
prepareData

Prepare input data to be used in active set algorithm