Joint Wald test of coefficients

Tests H0: R beta = r with the statistic (R b - r)' (R V R')^(-1) (R b - r), referred to a chi-squared distribution with nrow(R) degrees of freedom. The coefficients are chosen by name (terms), by a regular expression (pattern) or through an explicit restriction matrix R. Typical uses are the joint test of the spline columns of a regressor (does x matter at all), of the Mundlak means of a correlated random effects fit, or of the leads of an event study.

Usage

jointtest(object, terms = NULL, pattern = NULL, R = NULL, r = 0, vcov = NULL)

Arguments

object

a "panglm" fit

terms

character vector of coefficient names

pattern

regular expression selecting coefficient names (used when terms and R are NULL)

R

optional restriction matrix with one column per coefficient

r

right-hand side of the restrictions (recycled), default 0

vcov

NULL (the covariance stored on the fit) or a type passed to vcov.panglm(), e.g. "cluster"

Value

an object of class "panglm_jointtest": a list with statistic, df, p.value, terms and vcov_type

Validation

Checked against a hand computation of the Wald statistic, in both the terms and the R matrix forms, in the package tests.

See also

Other tests: lineartest(), pandispersiontest(), panhausman()

Examples

data(copd)
fit <- panglm(fev1 ~ splines::ns(crp, 3), data = copd,
              index = c("id", "visit"), model = "within", vcov = "cluster")
jointtest(fit, pattern = "crp")
#> 
#> Joint Wald test (vcov: cluster)
#> H0: all of splines::ns(crp, 3)1, splines::ns(crp, 3)2, splines::ns(crp, 3)3 are zero
#> Chi-squared = 37.27, df = 3, p-value = 4.031e-08
#>