confint: Confidence Intervals for Model Parameters

confintR Documentation

Confidence Intervals for Model Parameters


Computes confidence intervals for one or more parameters in a fitted model. There is a default and a method for objects inheriting from class "lm".


confint(object, parm, level = 0.95, ...)



a fitted model object.


a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.


the confidence level required.


additional argument(s) for methods.


confint is a generic function. The default method assumes normality, and needs suitable coef and vcov methods to be available. The default method can be called directly for comparison with other methods.

For objects of class "lm" the direct formulae based on t values are used.

There are stub methods in package stats for classes "glm" and "nls" which call those in package MASS (if installed): if the MASS namespace has been loaded, its methods will be used directly. (Those methods are based on profile likelihood.)


A matrix (or vector) with columns giving lower and upper confidence limits for each parameter. These will be labelled as (1-level)/2 and 1 - (1-level)/2 in % (by default 2.5% and 97.5%).

See Also

confint.glm and confint.nls in package MASS.


fit <- lm(100/mpg ~ disp + hp + wt + am, data = mtcars)
confint(fit, "wt")

## from example(glm)
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3, 1, 9); treatment <- gl(3, 3)
glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())
confint(glm.D93) # needs MASS to be installed
confint.default(glm.D93)  # based on asymptotic normality