constraint_matrices {clubSandwich}  R Documentation 
Helper functions to create common types of constraint matrices,
for use with Wald_test
to conduct Waldtype tests of linear
contrasts from a fitted regression model.
constrain_zero(constraints, coefs, reg_ex = FALSE)
constrain_equal(constraints, coefs, reg_ex = FALSE)
constrain_pairwise(constraints, coefs, reg_ex = FALSE, with_zero = FALSE)
constraints 
Set of constraints to test. Can be logical (using

coefs 
Vector of coefficient estimates, used to determine the column
dimension of the constraint matrix. Can be omitted if the function is
called inside 
reg_ex 
Logical indicating whether 
with_zero 
Logical indicating whether coefficients should also be
compared to zero. Defaults to 
Constraints can be specified as character vectors, regular
expressions (with reg_ex = TRUE
), integer vectors, or logical
vectors.
constrain_zero()
Creates a matrix that constrains a specified set of
coefficients to all be equal to zero.
constrain_equal()
Creates a matrix that constrains a specified set
of coefficients to all be equal.
constrain_pairwise()
Creates a list of constraint matrices
consisting of all pairwise comparisons between a specified set of
coefficients. If with_zero = TRUE
, then the list will also include a
set of constraint matrices comparing each coefficient to zero.
A matrix or list of matrices encoding the specified set of constraints.
data(Duncan, package = "carData")
Duncan$cluster < sample(LETTERS[1:8], size = nrow(Duncan), replace = TRUE)
Duncan_fit < lm(prestige ~ 0 + type + income + type:income + type:education, data=Duncan)
# Note that type:income terms are interactions because main effect of income is included
# but type:education terms are separate slopes for each unique level of type
Duncan_coefs < coef(Duncan_fit)
# The following are all equivalent
constrain_zero(constraints = c("typeprof:income","typewc:income"),
coefs = Duncan_coefs)
constrain_zero(constraints = ":income", coefs = Duncan_coefs,
reg_ex = TRUE)
constrain_zero(constraints = 5:6, coefs = Duncan_coefs)
constrain_zero(constraints = c(FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE),
coefs = Duncan_coefs)
# The following are all equivalent
constrain_equal(c("typebc:education","typeprof:education","typewc:education"),
Duncan_coefs)
constrain_equal(":education", Duncan_coefs, reg_ex = TRUE)
constrain_equal(7:9, Duncan_coefs)
constrain_equal(c(FALSE,FALSE,FALSE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE),
Duncan_coefs)
# Test pairwise equality of the education slopes
constrain_pairwise(":education", Duncan_coefs,
reg_ex = TRUE)
# Test pairwise equality of the income slopes, plus compare against zero
constrain_pairwise(":income", Duncan_coefs,
reg_ex = TRUE, with_zero = TRUE)