Contrast Matrices
contrMat.RdComputes contrast matrices for several multiple comparison procedures.
Usage
contrMat(n, type = c("Dunnett", "Tukey", "Sequen", "AVE",
"Changepoint", "Williams", "Marcus",
"McDermott", "UmbrellaWilliams", "GrandMean"),
base = 1)Details
Computes the requested matrix of contrasts for comparisons of mean levels. The general concept and specific choices are discussed by hothorn2008b and Bretz+Hothorn+Westfall_2010.
Examples
n <- c(10,20,30,40)
names(n) <- paste("group", 1:4, sep="")
contrMat(n) # Dunnett is default
#>
#> Multiple Comparisons of Means: Dunnett Contrasts
#>
#> group1 group2 group3 group4
#> group2 - group1 -1 1 0 0
#> group3 - group1 -1 0 1 0
#> group4 - group1 -1 0 0 1
contrMat(n, base = 2) # use second level as baseline
#>
#> Multiple Comparisons of Means: Dunnett Contrasts
#>
#> group1 group2 group3 group4
#> group1 - group2 1 -1 0 0
#> group3 - group2 0 -1 1 0
#> group4 - group2 0 -1 0 1
contrMat(n, type = "Tukey")
#>
#> Multiple Comparisons of Means: Tukey Contrasts
#>
#> group1 group2 group3 group4
#> group2 - group1 -1 1 0 0
#> group3 - group1 -1 0 1 0
#> group4 - group1 -1 0 0 1
#> group3 - group2 0 -1 1 0
#> group4 - group2 0 -1 0 1
#> group4 - group3 0 0 -1 1
contrMat(n, type = "Sequen")
#>
#> Multiple Comparisons of Means: Sequen Contrasts
#>
#> group1 group2 group3 group4
#> group2 - group1 -1 1 0 0
#> group3 - group2 0 -1 1 0
#> group4 - group3 0 0 -1 1
contrMat(n, type = "AVE")
#>
#> Multiple Comparisons of Means: AVE Contrasts
#>
#> group1 group2 group3 group4
#> C 1 1.0000 -0.2222 -0.3333 -0.4444
#> C 2 -0.1250 1.0000 -0.3750 -0.5000
#> C 3 -0.1429 -0.2857 1.0000 -0.5714
#> C 4 -0.1667 -0.3333 -0.5000 1.0000
contrMat(n, type = "Changepoint")
#>
#> Multiple Comparisons of Means: Changepoint Contrasts
#>
#> group1 group2 group3 group4
#> C 1 -1.0000 0.2222 0.3333 0.4444
#> C 2 -0.3333 -0.6667 0.4286 0.5714
#> C 3 -0.1667 -0.3333 -0.5000 1.0000
contrMat(n, type = "Williams")
#>
#> Multiple Comparisons of Means: Williams Contrasts
#>
#> group1 group2 group3 group4
#> C 1 -1 0.0000 0.0000 1.0000
#> C 2 -1 0.0000 0.4286 0.5714
#> C 3 -1 0.2222 0.3333 0.4444
contrMat(n, type = "Marcus")
#>
#> Multiple Comparisons of Means: Marcus Contrasts
#>
#> group1 group2 group3 group4
#> C 1 -1.0000 0.2222 0.3333 0.4444
#> C 2 -1.0000 0.0000 0.4286 0.5714
#> C 3 -0.3333 -0.6667 0.4286 0.5714
#> C 4 -1.0000 0.0000 0.0000 1.0000
#> C 5 -0.3333 -0.6667 0.0000 1.0000
#> C 6 -0.1667 -0.3333 -0.5000 1.0000
contrMat(n, type = "McDermott")
#>
#> Multiple Comparisons of Means: McDermott Contrasts
#>
#> group1 group2 group3 group4
#> C 1 -1.0000 1.0000 0.0 0
#> C 2 -0.3333 -0.6667 1.0 0
#> C 3 -0.1667 -0.3333 -0.5 1
### Umbrella-protected Williams contrasts, i.e. a sequence of
### Williams-type contrasts with groups of higher order
### stepwise omitted
contrMat(n, type = "UmbrellaWilliams")
#>
#> Multiple Comparisons of Means: UmbrellaWilliams Contrasts
#>
#> group1 group2 group3 group4
#> C 1 -1 0.0000 0.0000 1.0000
#> C 2 -1 0.0000 0.4286 0.5714
#> C 3 -1 0.2222 0.3333 0.4444
#> C 4 -1 0.0000 1.0000 0.0000
#> C 5 -1 0.4000 0.6000 0.0000
#> C 6 -1 1.0000 0.0000 0.0000
### comparison of each group with grand mean of all groups
contrMat(n, type = "GrandMean")
#>
#> Multiple Comparisons of Means: GrandMean Contrasts
#>
#> group1 group2 group3 group4
#> group1 0.9 -0.2 -0.3 -0.4
#> group2 -0.1 0.8 -0.3 -0.4
#> group3 -0.1 -0.2 0.7 -0.4
#> group4 -0.1 -0.2 -0.3 0.6