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library("multcomp")
set.seed(290875)
testdata <- data.frame(y = rnorm(21),
f1 <- factor(c(rep(c("A", "B", "C"), 7))),
f2 <- factor(c(rep("D", 10), rep("E", 11))),
x <- rnorm(21))
# one-way ANOVA
coef(amod <- aov(y ~ f1, data = testdata))
glht(amod, linfct = mcp(f1 = "Dunnett"))
# and a continuous covariable: ANCOVA
coef(lmod <- lm(y ~ f1 + x, data = testdata))
glht(lmod, linfct = mcp(f1 = "Dunnett"))
# ANCOVA with an additional factor as covariable
coef(lmod <- lm(y ~ f1 + f2 + x, data = testdata))
glht(lmod, linfct = mcp(f1 = "Dunnett"))
# and with interaction terms
coef(lmod <- lm(y ~ f1 + f2 + f2:f1 + x, data = testdata))
glht(lmod, linfct = mcp(f1 = "Dunnett"))
# with contrasts as expressions
glht(lmod, linfct = mcp(f1 = c("B - A = 0", "C - A = 0")))
tmp <- multcomp:::chrlinfct2matrix(c(l1 = "x1 - x2 = 2",
l2 = "x2 + 3 * x3 = 1"),
paste("x", 1:3, sep = ""))
stopifnot(max(abs(tmp$K - rbind(c(1, -1, 0), c(0, 1, 3)))) < sqrt(.Machine$double.eps))
stopifnot(max(abs(tmp$m - c(2, 1))) < sqrt(.Machine$double.eps))
### coef.survreg and vcov.survreg need special tuning
### thx to Z for pointing this out
if (require("survival")) {
smod <- survreg(Surv(futime, fustat) ~ ecog.ps + rx,
data = ovarian, dist = 'weibull')
K <- diag(length(coef(smod)))
rownames(K) <- names(coef(smod))
glht(smod, linfct = K)
}
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