Contrast Tests in 1D
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 class 'lmerModLmerTest' contest1D( model, L, rhs = 0, ddf = c("Satterthwaite", "Kenward-Roger"), confint = FALSE, level = 0.95, ... ) ## S3 method for class 'lmerMod' contest1D( model, L, rhs = 0, ddf = c("Satterthwaite", "Kenward-Roger"), confint = FALSE, level = 0.95, ... )
model |
a model object fitted with |
L |
a numeric (contrast) vector of the same length as
|
rhs |
right-hand-side of the statistical test, i.e. the hypothesized value (a numeric scalar). |
ddf |
the method for computing the denominator degrees of freedom.
|
confint |
include columns for lower and upper confidence limits? |
level |
confidence level. |
... |
currently not used. |
The t-value and associated p-value is for the hypothesis
L' β = rhs in which rhs may be non-zero
and β is fixef(model)
.
The estimated value ("Estimate"
) is L' β with associated
standard error and (optionally) confidence interval.
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.
Rune Haubo B. Christensen
# 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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