confint2: Confidence Intervals for Generalized Linear Models
In glmtoolbox: Set of Tools to Data Analysis using Generalized Linear Models

confint2

R Documentation

Confidence Intervals for Generalized Linear Models

Description

Computes confidence intervals based on Wald, likelihood-ratio, Rao's score or Terrell's gradient tests for a generalized linear model.

Usage

confint2(
  model,
  level = 0.95,
  test = c("wald", "lr", "score", "gradient"),
  digits = 5,
  verbose = TRUE
)

Arguments

`model`	an object of the class glm.
`level`	an (optional) value indicating the required confidence level. By default, `level` is set to be 0.95.
`test`	an (optional) character string indicating the required type of test. The available options are: Wald ("wald"), Rao's score ("score"), Terrell's gradient ("gradient"), and likelihood ratio ("lr") tests. By default, `test` is set to be "wald".
`digits`	an (optional) integer value indicating the number of decimal places to be used. By default, `digits` is set to be 5.
`verbose`	an (optional) logical indicating if should the report of results be printed. By default, `verbose` is set to be TRUE.

Details

The approximate 100(level)% confidence interval for \beta based on the test test is the set of values of \beta_0 for which the hypothesis H_0: \beta=\beta_0 versus H_1: \beta!=\beta_0 is not rejected at the approximate significance level of 100(1-level)%. The Wald, Rao's score and Terrell's gradient tests are performed using the expected Fisher information matrix.

Value

A matrix with so many rows as parameters in the linear predictor and two columns: "Lower limit" and "Upper limit".

References

Buse A. (1982) The Likelihood Ratio, Wald, and Lagrange Multiplier Tests: An Expository Note. The American Statistician 36, 153-157.

Terrell G.R. (2002) The gradient statistic. Computing Science and Statistics 34, 206 – 215.

Examples

###### Example 1: Fuel consumption of automobiles
Auto <- ISLR::Auto
fit1 <- glm(mpg ~ weight*horsepower, family=inverse.gaussian("log"), data=Auto)
confint2(fit1, test="lr")
confint2(fit1, test="score")

###### Example 2: Patients with burn injuries
burn1000 <- aplore3::burn1000
burn1000 <- within(burn1000, death <- factor(death, levels=c("Dead","Alive")))
fit2 <- glm(death ~ age*inh_inj + tbsa*inh_inj, family=binomial("logit"), data=burn1000)
confint2(fit2, test="lr")
confint2(fit2, test="gradient")

glmtoolbox documentation built on Oct. 10, 2023, 9:06 a.m.