coeftest {lmtest} | R Documentation |
coeftest
is a generic function for performing
z and (quasi-)t tests of estimated coefficients.
coeftest(x, vcov. = NULL, df = NULL, ...)
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 x$df.residual
and performs a z test if this is NULL . |
... |
further arguments passed to the methods. |
The generic function coeftest
currently has a default
method (which works in particular for "lm"
and
"glm"
objects) and a method for objects of class
"breakpointsfull"
(as computed by breakpointsfull
).
The default method assumes that a coef
methods exists,
such that coef(x)
yields the estimated coefficients.
To specify a covariance matrix vcov.
to be used, there
are three possibilities:
1. It is pre-computed and supplied in argument vcov.
.
2. A function for extracting the covariance matrix from
x
is supplied, e.g., vcovHC
or vcovHAC
from package sandwich.
3. vcov.
is set to NULL
, then it is assumed that
a vcov
method exists, such that vcov(x)
yields
a covariance matrix. For illustrations see below.
The degrees of freedom df
determine whether a normal
approximation is used or a t distribution with df
degrees
of freedoms is used. The default method uses x$df.residual
and if this is NULL
a z test is performed.
An object of class "coeftest"
which is essentially
a coefficient matrix with columns containing the estimates,
associated standard errors, test statistics and p values.
## 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")) }