README.md

In estimability: Tools for Assessing Estimability of Linear Predictions

title: "estimability" output: html_document date: '2022-07-03'

R package estimability: Support for determining estimability of linear functions

Features

• A nonest.basis() function is provided that determines a basis for the null space of a matrix. This may be used in conjunction with is.estble() to determine the estimability (within a tolerance) of a given linear function of the regression coefficients in a linear model.
• A set of epredict() methods are provided for lm, glm, and mlm objects. These work just like predict(), except an NA is returned for any cases that are not estimable. This is a useful alternative to the generic warning that "predictions from rank-deficient models are unreliable."
• A function estble.subspace() that projects a set of linear functions onto an estimable subspace (possibly of smaller dimension). This can be useful in creating a set of estimable contrasts for joint testing.
• Package developers may wish to import this package and incorporate estimability checks for their predict methods.

Installation

• To install latest version from CRAN, run

install.packages("estimability")

Release notes for the latest CRAN version are found at https://cran.r-project.org/package=estimability/NEWS -- or do news(package = "estimability") for notes on the version you have installed.

• To install the latest development version from Github, have the newest devtools package installed, then run

devtools::install_github("rvlenth/estimability", dependencies = TRUE)

For latest release notes on this development version, see the NEWS file

estimability documentation built on Aug. 5, 2022, 5:15 p.m.