VCA (version 1.2.1)

test.lsmeans: Perform t-Tests for Linear Contrasts on LS Means.

Description

Perform custom hypothesis tests on Least Squares Means (LS Means) of fixed effect.

Usage

test.lsmeans(obj, L, ddfm = c("contain", "residual", "satterthwaite"))

Arguments

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".

Details

This function is similar to function test.fixef and represents a convenient way of specifying linear contrasts of LS Means.

See Also

test.fixef, lsmeans

Examples

data(dataEP05A2_2)
ub.dat <- dataEP05A2_2[-c(11,12,23,32,40,41,42),]
fit <- anovaMM(y~day/(run), ub.dat)
lsm <- lsmeans(fit)
lsm
lc.mat <- getL(fit, 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(fit, 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)
lsm <- lsmeans(fit.anovaMM)
lsm
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)