library(lattice)
bwplot(Species ~ Sepal.Width, iris)
mm.treatment <- model.matrix(Sepal.Width ~ Species, iris)
head(mm.treatment)
## (Intercept) Speciesversicolor Speciesvirginica
## 1 1 0 0
## 2 1 0 0
## 3 1 0 0
## 4 1 0 0
## 5 1 0 0
## 6 1 0 0
tail(mm.treatment)
## (Intercept) Speciesversicolor Speciesvirginica
## 145 1 0 1
## 146 1 0 1
## 147 1 0 1
## 148 1 0 1
## 149 1 0 1
## 150 1 0 1
lm(Sepal.Width ~ Species, iris)
##
## Call:
## lm(formula = Sepal.Width ~ Species, data = iris)
##
## Coefficients:
## (Intercept) Speciesversicolor Speciesvirginica
## 3.428 -0.658 -0.454
mean(subset(iris, Species == "setosa")$Sepal.Width)
## [1] 3.428
mm.sum <- model.matrix(Sepal.Width ~ Species, iris, contrasts = list(Species = "contr.sum"))
head(mm.sum)
## (Intercept) Species1 Species2
## 1 1 1 0
## 2 1 1 0
## 3 1 1 0
## 4 1 1 0
## 5 1 1 0
## 6 1 1 0
tail(mm.sum)
## (Intercept) Species1 Species2
## 145 1 -1 -1
## 146 1 -1 -1
## 147 1 -1 -1
## 148 1 -1 -1
## 149 1 -1 -1
## 150 1 -1 -1
lm(Sepal.Width ~ Species, iris, contrasts = list(Species = "contr.sum"))
##
## Call:
## lm(formula = Sepal.Width ~ Species, data = iris, contrasts = list(Species = "contr.sum"))
##
## Coefficients:
## (Intercept) Species1 Species2
## 3.057 0.371 -0.287
mean(iris$Sepal.Width)
## [1] 3.057