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blm (version 1.2)

Binomial linear and linear-expit regression

Description

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

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Version

Install

install.packages('blm')

Monthly Downloads

364

Version

1.2

License

GPL (>= 2)

Maintainer

S A Kovalchik

Last Published

July 4th, 2011

Functions in blm (1.2)

predict

Get risk predictions for blm and lexpit objects.
ci

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

Dispersion statistics for blm and lexpit objects.
lexpit-class

Class "lexpit"
ssc

Strong Sufficient Condition check for binomial linear regression models
gof

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

Fit a binomial linear-expit regression model
expit

Inverse-logit function
coef

Get coefs from blm and lexpit objects.
logistic.dispersion

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

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

Binomial linear and linear-expit regression model
blm.rr

Estimate a relative risk from a binomial linear regression model
hosmerlem

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

Print coefficients of blm and lexpit model fit.
summary

Summary of blm and lexpit model fit.
vcov

Get variance-covariance from blm and lexpit objects.
blm

Fit a binomial linear regression model
grad

Data set on admission to graduate school
blm-class

Class "blm"
logistic.rd

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

Show blm and lexpit model fit.
vcovBoot

Get bootstrap variance-covariance from blm and lexpit objects.