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Compute the test of a one-dimensional (vector) contrast in a linear mixed model fitted with lmer from package lmerTest. The contrast should specify a linear function of the mean-value parameters, beta. The Satterthwaite or Kenward-Roger method is used to compute the (denominator) df for the t-test.
# S3 method for lmerModLmerTest
contest1D(model, L, rhs = 0,
ddf = c("Satterthwaite", "Kenward-Roger"), confint = FALSE,
level = 0.95, ...)# S3 method for lmerMod
contest1D(model, L, rhs = 0, ddf = c("Satterthwaite",
"Kenward-Roger"), confint = FALSE, level = 0.95, ...)
a model object fitted with lmer
from package
lmerTest, i.e., an object of class lmerModLmerTest
.
a numeric (contrast) vector of the same length as
fixef(model)
.
right-hand-side of the statistical test, i.e. the hypothesized value (a numeric scalar).
the method for computing the denominator degrees of freedom.
ddf="Kenward-Roger"
uses Kenward-Roger's method.
include columns for lower and upper confidence limits?
confidence level.
currently not used.
A data.frame
with one row and columns with "Estimate"
,
"Std. Error"
, "t value"
, "df"
, and "Pr(>|t|)"
(p-value). If confint = TRUE
"lower"
and "upper"
columns
are included before the p-value column.
The t-value and associated p-value is for the hypothesis
fixef(model)
.
The estimated value ("Estimate"
) is
contest
for a flexible
and general interface to tests of contrasts among fixed-effect parameters.
contestMD
is also available as a
direct interface for tests of multi degree-of-freedom contrast.
# NOT RUN {
# Fit model using lmer with data from the lme4-package:
data("sleepstudy", package="lme4")
fm <- lmer(Reaction ~ Days + (1 + Days|Subject), sleepstudy)
# Tests and CI of model coefficients are obtained with:
contest1D(fm, c(1, 0), confint=TRUE) # Test for Intercept
contest1D(fm, c(0, 1), confint=TRUE) # Test for Days
# Tests of coefficients are also part of:
summary(fm)
# Illustrate use of rhs argument:
contest1D(fm, c(0, 1), confint=TRUE, rhs=10) # Test for Days-coef == 10
# }
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