Perform t-Tests for Linear Contrasts on LS Means
Perform custom hypothesis tests on Least Squares Means (LS Means) of fixed effect.
test.lsmeans(
obj,
L,
ddfm = c("contain", "residual", "satterthwaite"),
quiet = FALSE
)obj |
(VCA) object |
L |
(matrix) specifying one or multiple custom hypothesis tests as linear contrasts of LS Means.
Which LS Means have to be used is inferred from the column names of matrix L, which need to
be in line with the naming of LS Means in function |
ddfm |
(character) string specifying the method used for computing the denominator degrees of freedom of t-tests of LS Means. Available methods are "contain", "residual", and "satterthwaite". |
quiet |
(logical) TRUE = will suppress any warning, which will be issued otherwise |
This function is similar to function test.fixef and represents a convenient way of specifying
linear contrasts of LS Means.
Andre Schuetzenmeister andre.schuetzenmeister@roche.com
## Not run:
data(dataEP05A2_2)
ub.dat <- dataEP05A2_2[-c(11,12,23,32,40,41,42),]
fit1 <- anovaMM(y~day/(run), ub.dat)
fit2 <- remlMM(y~day/(run), ub.dat)
lsm1 <- lsmeans(fit1)
lsm2 <- lsmeans(fit2)
lsm1
lsm2
lc.mat <- getL(fit1, c("day1-day2", "day3-day6"), "lsm")
lc.mat[1,c(1,2)] <- c(1,-1)
lc.mat[2,c(3,6)] <- c(1,-1)
lc.mat
test.lsmeans(fit1, lc.mat)
test.lsmeans(fit2, lc.mat)
# fit mixed model from the 'nlme' package
library(nlme)
data(Orthodont)
fit.lme <- lme(distance~Sex*I(age-11), random=~I(age-11)|Subject, Orthodont)
# re-organize data for using 'anovaMM'
Ortho <- Orthodont
Ortho$age2 <- Ortho$age - 11
Ortho$Subject <- factor(as.character(Ortho$Subject))
# model without intercept
fit.anovaMM <- anovaMM(distance~Sex+Sex:age2+(Subject)+(Subject):age2-1, Ortho)
fit.remlMM1 <- remlMM( distance~Sex+Sex:age2+(Subject)+(Subject):age2-1, Ortho)
fit.remlMM2 <- remlMM( distance~Sex+Sex:age2+(Subject)+(Subject):age2-1, Ortho, cov=FALSE)
lsm0 <- lsmeans(fit.anovaMM)
lsm1 <- lsmeans(fit.remlMM1)
lsm2 <- lsmeans(fit.remlMM2)
lsm0
lsm1
lsm2
lc.mat <- matrix(c(1,-1), nrow=1, dimnames=list("int.Male-int.Female", c("SexMale", "SexFemale")))
lc.mat
test.lsmeans(fit.anovaMM, lc.mat)
test.lsmeans(fit.remlMM1, lc.mat)
test.lsmeans(fit.remlMM2, lc.mat)
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