Learn R Programming
⚠️There's a newer version (2022.0.0.1) of this package.Take me there.

blm (version 2011.1.3)

Binomial linear and linear-expit regression

Description

General additive regression models for binary cohort data which use constrained maximum likelihood for estimation.

Copy Link

Version

Install

install.packages('blm')

Monthly Downloads

364

Version

2011.1.3

License

GPL (>= 2)

Maintainer

S A Kovalchik

Last Published

August 19th, 2011

Functions in blm (2011.1.3)

blm

Fit a binomial linear regression model
blm-class

Class "blm"
summary

Summary of blm and lexpit model fit.
logistic.rd

Estimate a risk difference between two subject types from a logistic regression model
expit

Inverse-logit function
hosmerlem

Hosmer-Lemeshow goodness-of-fit for logistic regression model
gof

Get goodness-of-fit statistic blm and lexpit objects.
vcovBoot

Get bootstrap variance-covariance from blm and lexpit objects.
print

Print coefficients of blm and lexpit model fit.
logistic.baseline

Estimate an absolute risk from a logistic regression model
logistic.dispersion

Computes deviance and Pearson's chi-squared statistica for a logisitc model fit with glm.
coef

Get coefs from blm and lexpit objects.
lexpit-class

Class "lexpit"
ci

Compute confidence interval for linear combination of estimates from a blm and lexpit fit.
predict

Get risk predictions for blm and lexpit objects.
dispersion

Dispersion statistics for blm and lexpit objects.
show

Show blm and lexpit model fit.
grad

Data set on admission to graduate school
logistic.rr

Estimate a relative risk from a logistic regression model
blm-package

Binomial linear and linear-expit regression model
vcov

Get variance-covariance from blm and lexpit objects.
blm.rr

Estimate a relative risk from a binomial linear regression model
lexpit

Fit a binomial linear-expit regression model