lmtest (version 0.9-9)

coeftest: Testing Estimated Coefficients

Description

coeftest is a generic function for performing z and (quasi-)t tests of estimated coefficients.

Usage

coeftest(x, vcov = NULL, df = NULL, ...)

Arguments

x

an object (for details see below).

vcov

a specification of the covariance matrix of the estimated coefficients. This can be specified as a matrix or as a function yielding a matrix when applied to x.

df

the degrees of freedom to be used. If this is a finite positive number a t test with df degrees of freedom is performed. In all other cases, a z test (using a normal approximation) is performed. By default it tries to use

...

further arguments passed to the methods.

Value

• An object of class "coeftest" which is essentially a coefficient matrix with columns containing the estimates, associated standard errors, test statistics and p values.

Details

The generic function coeftest currently has a default method (which works in particular for "lm" and "glm" objects) and a method for objects of class "breakpointsfull" (as computed by breakpointsfull).

The default method assumes that a coef methods exists, such that coef(x) yields the estimated coefficients.

To specify a covariance matrix vcov to be used, there are three possibilities: 1. It is pre-computed and supplied in argument vcov. 2. A function for extracting the covariance matrix from x is supplied, e.g., vcovHC or vcovHAC from package sandwich. 3. vcov is set to NULL, then it is assumed that a vcov method exists, such that vcov(x) yields a covariance matrix. For illustrations see below.

The degrees of freedom df determine whether a normal approximation is used or a t distribution with df degrees of freedoms is used. The default method uses x$df.residual and if this is NULL a z test is performed.

See Also

lm

Examples

## load data and fit model
data(Mandible)
fm <- lm(length ~ age, data=Mandible, subset=(age <= 28))

## the following commands lead to the same tests:
summary(fm)
coeftest(fm)

## a z test (instead of a t test) can be performed by
coeftest(fm, df = Inf)

if(require(sandwich)) {
## a different covariance matrix can be also used:
## either supplied as a function
coeftest(fm, df = Inf, vcov = vcovHC)
## or as a matrix
coeftest(fm, df = Inf, vcov = vcovHC(fm, type = "HC0"))
}